Triple
T9576897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haridwar district |
E231067
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Laksar
Laksar is a town in the Haridwar district of Uttarakhand, India, known primarily as a significant railway junction connecting various parts of northern India.
|
E809190
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Laksar | Statement: [Haridwar district, containsTown, Laksar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laksar Context triple: [Haridwar district, containsTown, Laksar]
-
A.
Ladwa
Ladwa is a town in the northern Indian state of Haryana, known as a local commercial and agricultural hub within the Kurukshetra region.
-
B.
Saida Khera
Saida Khera is a village in Punjab, India, known in folklore as a setting linked to the legendary love story of Heer Ranjha.
-
C.
Lehri
Lehri is a town and administrative area in Pakistan’s Balochistan province, known for its rural character and role as a local hub within the region.
-
D.
Karimabad
Karimabad is a neighborhood in Karachi, Pakistan, known for its bustling markets and central urban location within the city.
-
E.
Karimabad
Karimabad is a picturesque town in northern Pakistan’s Hunza region, known for its stunning mountain scenery, historic forts, and role as a popular base for trekkers and tourists.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Laksar Triple: [Haridwar district, containsTown, Laksar]
Generated description
Laksar is a town in the Haridwar district of Uttarakhand, India, known primarily as a significant railway junction connecting various parts of northern India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laksar Target entity description: Laksar is a town in the Haridwar district of Uttarakhand, India, known primarily as a significant railway junction connecting various parts of northern India.
-
A.
Ladwa
Ladwa is a town in the northern Indian state of Haryana, known as a local commercial and agricultural hub within the Kurukshetra region.
-
B.
Saida Khera
Saida Khera is a village in Punjab, India, known in folklore as a setting linked to the legendary love story of Heer Ranjha.
-
C.
Lehri
Lehri is a town and administrative area in Pakistan’s Balochistan province, known for its rural character and role as a local hub within the region.
-
D.
Karimabad
Karimabad is a neighborhood in Karachi, Pakistan, known for its bustling markets and central urban location within the city.
-
E.
Karimabad
Karimabad is a picturesque town in northern Pakistan’s Hunza region, known for its stunning mountain scenery, historic forts, and role as a popular base for trekkers and tourists.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99ac17a48190bb8448394f22b1e9 |
completed | April 1, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d16155b3288190ac135c3a1e58cc7e |
completed | April 4, 2026, 7:07 p.m. |
| NEDg | Description generation | batch_69d161e6a1308190932c8386e1c24f2e |
completed | April 4, 2026, 7:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d165a8c80081909e4d0837cbaabf95 |
completed | April 4, 2026, 7:25 p.m. |
Created at: March 30, 2026, 8:05 p.m.