Triple
T18306767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheffield F.C. |
E438505
|
entity |
| Predicate | fifaOrderOfMeritYear |
P131270
|
FINISHED |
| Object | 2004 |
—
|
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: 2004 | Statement: [Sheffield F.C., fifaOrderOfMeritYear, 2004]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fifaOrderOfMeritYear Context triple: [Sheffield F.C., fifaOrderOfMeritYear, 2004]
-
A.
fifaHighestRanking
Indicates the highest position an entity has ever achieved in the official FIFA world rankings.
-
B.
fifaRankingBestSpanStart
Indicates the starting point in time when an entity begins its best (highest) FIFA ranking span.
-
C.
fifaRankingBestSpanEnd
Indicates the ending point in time of the period during which an entity held its highest FIFA ranking.
-
D.
fifaRankingHighest
Indicates that the subject has the highest FIFA ranking among a specified group or within a given context.
-
E.
fifaRankingWorstYear
Indicates the year in which an entity (such as a team or player) reached its lowest (worst) position in the FIFA rankings.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021519a481908a9b6561946f1c65 |
completed | April 19, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:35 a.m.