Triple
T19826506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takelot II |
E476338
|
entity |
| Predicate | personalName |
P24312
|
FINISHED |
| Object |
Takelot
Takelot is an ancient Egyptian royal name most notably borne by Takelot II, a pharaoh of the 22nd Dynasty during the Third Intermediate Period.
|
E1397316
|
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: Takelot | Statement: [Takelot II, personalName, Takelot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takelot Context triple: [Takelot II, personalName, Takelot]
-
A.
Keliko
Keliko is a Central Sudanic language spoken by the Keliko people primarily in South Sudan and the Democratic Republic of the Congo.
-
B.
Taloot
Taloot is a coastal barangay of the municipality of Argao in Cebu, Philippines.
-
C.
Tirhuta
Tirhuta is a historical Brahmic script traditionally used for writing the Maithili language in the Mithila region of India and Nepal.
-
D.
Tahawus
Tahawus is a remote hamlet in New York’s Adirondack Mountains known for its historic iron mining operations and proximity to High Peaks wilderness areas.
-
E.
Tasambeker
Tasambeker is a character from the Doctor Who serial "Revelation of the Daleks," serving as a mortuary worker whose loyalty and emotions are manipulated amid the story’s dark events.
- 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: Takelot Triple: [Takelot II, personalName, Takelot]
Generated description
Takelot is an ancient Egyptian royal name most notably borne by Takelot II, a pharaoh of the 22nd Dynasty during the Third Intermediate Period.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Takelot Target entity description: Takelot is an ancient Egyptian royal name most notably borne by Takelot II, a pharaoh of the 22nd Dynasty during the Third Intermediate Period.
-
A.
Keliko
Keliko is a Central Sudanic language spoken by the Keliko people primarily in South Sudan and the Democratic Republic of the Congo.
-
B.
Taloot
Taloot is a coastal barangay of the municipality of Argao in Cebu, Philippines.
-
C.
Tirhuta
Tirhuta is a historical Brahmic script traditionally used for writing the Maithili language in the Mithila region of India and Nepal.
-
D.
Tahawus
Tahawus is a remote hamlet in New York’s Adirondack Mountains known for its historic iron mining operations and proximity to High Peaks wilderness areas.
-
E.
Tasambeker
Tasambeker is a character from the Doctor Who serial "Revelation of the Daleks," serving as a mortuary worker whose loyalty and emotions are manipulated amid the story’s dark events.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656cb20788190b9deac6b8af6a55d |
completed | April 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ccd3f4308190879396a336026a83 |
completed | May 16, 2026, 1:48 a.m. |
| NEDg | Description generation | batch_6a07cf6713108190a887b91e26da1ca5 |
completed | May 16, 2026, 1:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d008357081908bff9ebfbda41ba1 |
completed | May 16, 2026, 2:01 a.m. |
Created at: April 10, 2026, 1:50 p.m.