Triple
T28566231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Mallard |
E722684
|
entity |
| Predicate | servedInWarInBackstory |
P170730
|
FINISHED |
| Object | Gulf War |
—
|
NE NERFINISHED |
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: Gulf War | Statement: [Donald Mallard, servedInWarInBackstory, Gulf War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedInWarInBackstory Context triple: [Donald Mallard, servedInWarInBackstory, Gulf War]
-
A.
militaryConflictInBackstory
Indicates that a character or entity has a history involving a military conflict that occurred prior to the main events or timeline being described.
-
B.
hadMilitaryServiceFrom
Indicates that an entity performed or was engaged in military service starting from a specified point in time.
-
C.
placeOfMilitaryService
Indicates the location or institution where a person performed their military service.
-
D.
hadMilitaryFollowing
Indicates that an entity was supported or backed by a group of military personnel or forces.
-
E.
warServedInFictionally
chosen
Indicates that a fictional character is depicted as having served in a particular war within a narrative or story.
- F. None of above.
Provenance (3 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_69f01a5f69d08190ad5c0d2167078dec |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: April 28, 2026, 4:07 a.m.