Triple
T38399224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lesser Zhuz |
E900848
|
entity |
| Predicate | notableKhan |
P204638
|
FINISHED |
| Object | Abulkhair Khan |
E2002887
|
NE FINISHED |
How this triple was built (2 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: Abulkhair Khan | Statement: [Lesser Zhuz, notableKhan, Abulkhair Khan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableKhan Context triple: [Lesser Zhuz, notableKhan, Abulkhair Khan]
-
A.
notablePupil
Indicates that one person is a distinguished or noteworthy student or protégé of another person.
-
B.
notableStudent
Indicates that a person is a distinguished or particularly significant student of another individual or institution.
-
C.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
D.
notableDuo
Indicates that two entities are widely recognized together as a famous or significant pair.
-
E.
notableTeaching
Indicates that one entity is recognized for having taught, instructed, or educated another entity in a notable or significant way.
- 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_69f76e6071a081909eea7a670d21420c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a42157eaa2081908fe15dd71f7b9589 |
completed | June 29, 2026, 6:49 a.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:31 p.m.