Triple
T27326972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qu Yunxia |
E689677
|
entity |
| Predicate | olympicMedalInEvent |
P7487
|
FINISHED |
| Object | women’s 3000 metres |
—
|
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: women’s 3000 metres | Statement: [Qu Yunxia, olympicMedalInEvent, women’s 3000 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: olympicMedalInEvent Context triple: [Qu Yunxia, olympicMedalInEvent, women’s 3000 metres]
-
A.
olympicGoldMedalInEvent
Indicates that an entity has won an Olympic gold medal in a specified sporting event.
-
B.
OlympicMedalEvent
Indicates that an entity represents a specific Olympic Games event in which medals are awarded.
-
C.
OlympicMedal
chosen
Indicates that an entity has been awarded an Olympic medal in a specific event or discipline.
-
D.
medalEventsFor
Indicates a relationship where one entity lists or specifies the medal-awarding events associated with another entity.
-
E.
typeOfMedalEvent
Indicates the specific medal category (e.g., gold, silver, bronze) associated with a particular event.
- 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_69ef355d4cb08190ab032c0a2e7d3753 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 11:36 a.m.