Triple
T36679407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Stand |
E905634
|
entity |
| Predicate | hasUseDuring |
P4341
|
FINISHED |
| Object | professional rugby matches |
—
|
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: professional rugby matches | Statement: [North Stand, hasUseDuring, professional rugby matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUseDuring Context triple: [North Stand, hasUseDuring, professional rugby matches]
-
A.
usedDuring
chosen
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
-
B.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
-
C.
areUsedSince
Indicates that entities have been in use continuously starting from a specified point in time.
-
D.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
E.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, or context.
- 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.