Triple
T2504575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Spitz won seven gold medals in swimming |
E52547
|
entity |
| Predicate | previousRecordForGoldsAtSingleGames |
P40840
|
FINISHED |
| Object | surpassed |
—
|
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: surpassed | Statement: [Mark Spitz won seven gold medals in swimming, previousRecordForGoldsAtSingleGames, surpassed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousRecordForGoldsAtSingleGames Context triple: [Mark Spitz won seven gold medals in swimming, previousRecordForGoldsAtSingleGames, surpassed]
-
A.
worldChampionshipGoldMedals
Indicates the number of gold medals an entity has won at world championship competitions.
-
B.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
-
C.
historicalPredecessorHasOlympicGoldMedals
Indicates that the earlier historical counterpart of an entity has won one or more Olympic gold medals.
-
D.
WorldChampionshipGoldMedalYear
Indicates the specific year in which an entity won a gold medal at a world championship event.
-
E.
goldMedalGameFor
Indicates that the referenced game is the one in which the gold medal is contested or awarded for a particular event or competition.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd65c9d508190957285a078698ed2 |
completed | March 7, 2026, 7:40 a.m. |
Created at: March 6, 2026, 9:46 p.m.