Triple
T2895030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huddersfield Town A.F.C. |
E63916
|
entity |
| Predicate | consecutiveLeagueTitlesPeriod |
P43847
|
FINISHED |
| Object | 1923–24 |
—
|
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: 1923–24 | Statement: [Huddersfield Town A.F.C., consecutiveLeagueTitlesPeriod, 1923–24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consecutiveLeagueTitlesPeriod Context triple: [Huddersfield Town A.F.C., consecutiveLeagueTitlesPeriod, 1923–24]
-
A.
consecutiveWinningSeasons
Indicates that an entity (such as a team or individual) has achieved winning seasons in back-to-back or uninterrupted consecutive years.
-
B.
mostConsecutiveWinsCount
Indicates the highest number of wins achieved in a row within a given sequence or context.
-
C.
consecutive50GoalSeasons
Indicates that an entity has achieved 50 or more goals in each of multiple consecutive seasons.
-
D.
consecutiveWinsInSeason
Indicates that one entity achieved a specified number of back-to-back victories within a single season.
-
E.
championshipDroughtLengthYears
Indicates the number of years that have elapsed since an entity last won a championship.
- 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_69ab4c45822c8190830c5f2bb97bcfd0 |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe06509808190b673222b9ae3d599 |
completed | March 7, 2026, 8:23 a.m. |
| PD | Predicate disambiguation | batch_69abdd17bcdc8190aa47274a50ba4ad4 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde0f4c648190b9812e64f30c39da |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 10:08 p.m.