Triple
T7435531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dinner Party |
E171602
|
entity |
| Predicate | numberOfHonoredWomen |
P76390
|
FINISHED |
| Object | 39 at the table |
—
|
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: 39 at the table | Statement: [The Dinner Party, numberOfHonoredWomen, 39 at the table]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHonoredWomen Context triple: [The Dinner Party, numberOfHonoredWomen, 39 at the table]
-
A.
honoredThrough
Indicates that one entity is recognized or commemorated by means of another entity, event, or action.
-
B.
honoredOn
Indicates that an entity is formally recognized, celebrated, or commemorated on a specific date or occasion.
-
C.
alsoHonoredAs
Indicates that an entity is additionally recognized or celebrated under another title, role, or form of honor beyond its primary designation.
-
D.
hadWomenOrganization
Indicates that an entity was associated with or involved in an organization focused on women or women’s issues.
-
E.
admittedWomen
Indicates that an entity allowed or accepted women into a place, group, institution, or event.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f328cf6081908bea065639fd3620 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0be2b1c8190bea06100a7caef2b |
completed | March 27, 2026, 9:03 p.m. |
Created at: March 27, 2026, 3:13 p.m.