Triple
T11141453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | decathlon |
E263563
|
entity |
| Predicate | womenEquivalent |
P1613
|
FINISHED |
| Object | heptathlon |
—
|
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: heptathlon | Statement: [decathlon, womenEquivalent, heptathlon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenEquivalent Context triple: [decathlon, womenEquivalent, heptathlon]
-
A.
hasFemaleEquivalent
chosen
Indicates that one entity serves as the female counterpart or equivalent of another entity.
-
B.
femaleMass
Indicates that the subject has a mass value specifically associated with its female form or female population.
-
C.
womenSection
Indicates that something is designated as belonging to, located in, or associated with the women's section or area.
-
D.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
E.
maleEquivalent
Indicates that one entity is the corresponding male counterpart or equivalent of another entity.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8623158819096ad1678fa9e72bb |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.