Triple
T7435532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dinner Party |
E171602
|
entity |
| Predicate | numberOfAdditionalWomenHonored |
P4086
|
FINISHED |
| Object | over 900 on the heritage floor |
—
|
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: over 900 on the heritage floor | Statement: [The Dinner Party, numberOfAdditionalWomenHonored, over 900 on the heritage floor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAdditionalWomenHonored Context triple: [The Dinner Party, numberOfAdditionalWomenHonored, over 900 on the heritage floor]
-
A.
admittedWomen
Indicates that an entity allowed or accepted women into a place, group, institution, or event.
-
B.
alsoHonoredAs
Indicates that an entity is additionally recognized or celebrated under another title, role, or form of honor beyond its primary designation.
-
C.
hadWomenOrganization
Indicates that an entity was associated with or involved in an organization focused on women or women’s issues.
-
D.
notableFemaleWinner
Indicates that the subject is a female who has achieved a notable or distinguished victory in the specified context.
-
E.
numberOfCommemoratedPersons
chosen
Indicates the count of distinct persons who are commemorated or honored in a given context or 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_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. |
Created at: March 27, 2026, 3:13 p.m.