Triple
T38334048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michelle McCool |
E1037901
|
entity |
| Predicate | firstToHoldTitle |
P153898
|
FINISHED |
| Object | WWE Divas Championship |
E385134
|
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: WWE Divas Championship | Statement: [Michelle McCool, firstToHoldTitle, WWE Divas Championship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstToHoldTitle Context triple: [Michelle McCool, firstToHoldTitle, WWE Divas Championship]
-
A.
isYoungestToHoldTitle
Indicates that the subject is the youngest individual ever to have held the specified title or position.
-
B.
wasTitleHeldBy
Indicates that a specific title, position, or rank was held or occupied by a particular entity (such as a person or organization).
-
C.
first_holder
chosen
Indicates that the subject is the earliest or original holder or possessor of the specified object, title, or right.
-
D.
heldMostPrestigiousTitleIn
Indicates that one entity possessed the highest or most esteemed title within a particular domain, group, or context for some period of time.
-
E.
firstInOfficeTo
Indicates that one entity was the earliest or first to hold a particular office or position in relation to another entity or context.
- F. None of above.
Provenance (4 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_69f76e20d65c81909619ac0dd85c56f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41c275625881908e1153d4064a86d9 |
completed | June 29, 2026, 12:55 a.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:30 p.m.