Triple
T2504566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Spitz won seven gold medals in swimming |
E52547
|
entity |
| Predicate | numberOfGoldMedals |
P35180
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Mark Spitz won seven gold medals in swimming, numberOfGoldMedals, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoldMedals Context triple: [Mark Spitz won seven gold medals in swimming, numberOfGoldMedals, 7]
-
A.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
-
B.
totalOlympicGoldMedals
chosen
Indicates the total number of Olympic gold medals that an entity has won.
-
C.
totalOlympicMedals
Indicates the total number of Olympic medals an entity has earned across all Games and events.
-
D.
topGoldMedalCountry
Indicates that a country is the one with the highest number of gold medals in a given competition or context.
-
E.
OlympicMedal
Indicates that an entity has been awarded an Olympic medal in a specific event or discipline.
- F. None of above.
Provenance (3 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_69abd1cd2db0819087d21ec49ffd9585 |
completed | March 7, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69abd0bba5348190bb4637d3165cb339 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.