Triple
T34826073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Braves |
E1003924
|
entity |
| Predicate | hasFemaleCounterpartNickname |
P1613
|
FINISHED |
| Object | Lady Braves |
—
|
NE NERFINISHED |
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: Lady Braves | Statement: [Braves, hasFemaleCounterpartNickname, Lady Braves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFemaleCounterpartNickname Context triple: [Braves, hasFemaleCounterpartNickname, Lady Braves]
-
A.
hasCounterpartNickname
Indicates that one entity is used as an alternative or counterpart nickname for another entity.
-
B.
hasFemaleEquivalent
chosen
Indicates that one entity serves as the female counterpart or equivalent of another entity.
-
C.
femaleCounterpartOf
Indicates that one entity is the female equivalent or corresponding counterpart of another entity within a given role, relationship, or category.
-
D.
hasGivenNameCounterpart
Indicates that one entity is the given-name (first-name) counterpart or variant of another entity, typically linking related personal names.
-
E.
usesNicknameForWomen'sTeams
Indicates that an organization or context refers to its women’s sports teams using a distinct nickname (often different from or modified relative to the men’s teams’ nickname).
- 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_69f76db7d1b4819093bd4912d80d845d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4 p.m.