Triple
T11543174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D.Va |
E273721
|
entity |
| Predicate | formerRoleInOverwatch |
P99959
|
FINISHED |
| Object | tank |
—
|
LITERAL 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: tank | Statement: [D.Va, formerRoleInOverwatch, tank]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerRoleInOverwatch Context triple: [D.Va, formerRoleInOverwatch, tank]
-
A.
formerCharacter
Indicates that an entity was once a character in a work or series but is no longer an active or current character.
-
B.
formerMilitaryRole
Indicates that an entity previously held, but no longer holds, a specific military role or position.
-
C.
roleInWatchmen
Indicates that one entity has a specific role or function within the context of the work "Watchmen" in relation to the other entity.
-
D.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
E.
roleInFranchiseHistory
Indicates the specific function, position, or contribution an entity has within the historical development or timeline of a franchise.
- F. None of above. chosen
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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d886e09eec8190894069d86b79183d |
completed | April 10, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69d8087cbe7c819085680f3d67ccc978 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822ef46988190a1c360da4ee14fef |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:37 p.m.