Triple
T5870422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steel City derby |
E130501
|
entity |
| Predicate | firstCompetitiveDerbyYear |
P67633
|
FINISHED |
| Object | 1893 |
—
|
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: 1893 | Statement: [Steel City derby, firstCompetitiveDerbyYear, 1893]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstCompetitiveDerbyYear Context triple: [Steel City derby, firstCompetitiveDerbyYear, 1893]
-
A.
firstSeasonOfRivalry
Indicates the season in which a particular rivalry between entities first began or was officially recognized.
-
B.
divisionalRivalrySince
Indicates that two entities have been in a state of divisional rivalry starting from a specified point in time.
-
C.
firstKnownTournamentYear
Indicates the year in which a tournament was first known to have been held.
-
D.
firstIntercollegiateGameDate
Indicates the calendar date on which an entity participated in its first intercollegiate game or match.
-
E.
firstWinnerYear
Indicates the year in which an entity first won a particular competition, award, or title.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c044fe17d08190b9bf47b13863ef52 |
completed | March 22, 2026, 7:37 p.m. |
Created at: March 22, 2026, 3:56 p.m.