Triple
T13543847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shoremen |
E323459
|
entity |
| Predicate | hasCounterpartNickname |
P110281
|
FINISHED |
| Object | Shorewomen |
—
|
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: Shorewomen | Statement: [Shoremen, hasCounterpartNickname, Shorewomen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCounterpartNickname Context triple: [Shoremen, hasCounterpartNickname, Shorewomen]
-
A.
hasCounterpart
Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
-
B.
counterpartEnglishName
Indicates that an entity has a corresponding counterpart whose name is given in English.
-
C.
counterpartRelation
Indicates a reciprocal relationship where two entities serve as corresponding or equivalent counterparts to each other in a given context.
-
D.
isOfficialNicknameOf
Indicates that one name is the formally recognized nickname or informal moniker used to refer to another entity.
-
E.
isOppositionCounterpartOf
Indicates a relationship where one entity serves as the opposing or counterpart force, side, or position to another within a conflict, competition, or contrast.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae13bec4819084c1770638c00ed9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbbb8c77dc8190b7bd803b5e168d23 |
completed | April 12, 2026, 3:34 p.m. |
Created at: April 9, 2026, 9:45 p.m.