Triple
T16552607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warrington Wolves |
E402108
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | WAR |
E402109
|
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: WAR | Statement: [Warrington Wolves, hasAbbreviation, WAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WAR Context triple: [Warrington Wolves, hasAbbreviation, WAR]
-
A.
WAR
chosen
WAR is the commonly used abbreviation for the Warrington Wolves, a professional rugby league club based in Warrington, England.
-
B.
WAR
WAR is the National Rail station code for Ware railway station in Hertfordshire, England.
-
C.
War
War is a small town in McDowell County, West Virginia, known as one of the southernmost communities in the state and for its history as a coal mining town.
-
D.
War
"War" is a musical track from the film score of James Cameron's 2009 science fiction epic "Avatar," composed by James Horner.
-
E.
War
"War" is a film featuring Swiss actress Ella Rumpf in a prominent role.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fc6735481908b59bbf80fb3469b |
completed | April 18, 2026, 9:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0067b87b608190950b8f14e6aceed3 |
completed | May 10, 2026, 11:10 a.m. |
Created at: April 10, 2026, 5:15 a.m.