Triple
T3847710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Phelps won eight gold medals in swimming |
E85211
|
entity |
| Predicate | hasMedalCount |
P51907
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Michael Phelps won eight gold medals in swimming, hasMedalCount, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedalCount Context triple: [Michael Phelps won eight gold medals in swimming, hasMedalCount, 8]
-
A.
hasMultipleMedalsPerYear
Indicates that an entity has been awarded more than one medal within the same calendar year.
-
B.
wonMedalAt
Indicates that an entity received a medal as a result of participating in a specific event or competition.
-
C.
includesMedal
Indicates that an entity’s set, collection, or record contains or features a particular medal as one of its elements.
-
D.
medalIn
Indicates that an entity has received a medal or award in a particular event, field, or competition.
-
E.
hasTrophyStatus
Indicates that an entity possesses a particular trophy-related status or classification.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcc8a0481909c35161336bdfbf9 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee8d9b328819080158be59e5bcc97 |
completed | March 9, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:18 p.m.