Triple
T17719700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hama Governorate |
E442298
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Mahardah
Mahardah is a city in northwestern Syria known for its predominantly Christian population and its location near the Orontes River.
|
E1297771
|
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: Mahardah | Statement: [Hama Governorate, contains, Mahardah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahardah Context triple: [Hama Governorate, contains, Mahardah]
-
A.
Kahalgaon
Kahalgaon is a town in the Bhagalpur district of Bihar, India, known for its thermal power station and proximity to the historic Vikramshila university site.
-
B.
Shahdol
Shahdol is a city in the eastern part of Madhya Pradesh, India, known as an administrative and commercial center for the surrounding coal- and forest-rich region.
-
C.
Saharsa
Saharsa is a city in the northeastern Indian state of Bihar, known as a major agricultural and commercial center in the Kosi river region.
-
D.
Sagarhawa
Sagarhawa is an archaeological and historical site in Nepal’s Lumbini region, associated with ancient Buddhist heritage.
-
E.
Maharajganj
Maharajganj is a city in the Purvanchal region of Uttar Pradesh, India, serving as an administrative and commercial center near the Indo-Nepal border.
- 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: Mahardah Triple: [Hama Governorate, contains, Mahardah]
Generated description
Mahardah is a city in northwestern Syria known for its predominantly Christian population and its location near the Orontes River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mahardah Target entity description: Mahardah is a city in northwestern Syria known for its predominantly Christian population and its location near the Orontes River.
-
A.
Kahalgaon
Kahalgaon is a town in the Bhagalpur district of Bihar, India, known for its thermal power station and proximity to the historic Vikramshila university site.
-
B.
Shahdol
Shahdol is a city in the eastern part of Madhya Pradesh, India, known as an administrative and commercial center for the surrounding coal- and forest-rich region.
-
C.
Saharsa
Saharsa is a city in the northeastern Indian state of Bihar, known as a major agricultural and commercial center in the Kosi river region.
-
D.
Sagarhawa
Sagarhawa is an archaeological and historical site in Nepal’s Lumbini region, associated with ancient Buddhist heritage.
-
E.
Maharajganj
Maharajganj is a city in the Purvanchal region of Uttar Pradesh, India, serving as an administrative and commercial center near the Indo-Nepal border.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e474844ff48190b1cf181eb9c113d9 |
completed | April 19, 2026, 6:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0328ff60388190af4f7fe30a4c1d7c |
completed | May 12, 2026, 1:19 p.m. |
| NEDg | Description generation | batch_6a032b79b55c81909ad92206c44402f5 |
completed | May 12, 2026, 1:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a032c1200808190982b03ba82dda8cb |
completed | May 12, 2026, 1:33 p.m. |
Created at: April 10, 2026, 10:07 a.m.