Triple
T24564628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2005 British & Irish Lions tour to New Zealand |
E607747
|
entity |
| Predicate | matchesLostByLions |
P156353
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [2005 British & Irish Lions tour to New Zealand, matchesLostByLions, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchesLostByLions Context triple: [2005 British & Irish Lions tour to New Zealand, matchesLostByLions, 4]
-
A.
matchesLostLeague
Indicates the number of league matches that an entity has lost.
-
B.
gamesLostBy
Indicates the number of games that one entity has been defeated in by another entity.
-
C.
goalsByLosingTeam
Indicates the number of goals scored by the team that ultimately lost the match.
-
D.
LionsTourParticipation
Indicates participation in a British & Irish Lions rugby tour, linking a person or team to their involvement in that specific touring event.
-
E.
mostGamesLostBy
Indicates that one entity holds the record for having lost the greatest number of games to another entity.
- 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_69e2c4cc35a48190990b7571bc086df8 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8f9d0f881909afc04537c32f76b |
completed | April 30, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a846c5bc81909ba50cee483bea91 |
completed | April 30, 2026, 12:54 a.m. |
Created at: April 18, 2026, 2:28 a.m.