Triple
T22136045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parisian salon at Rue de Courcelles |
E547030
|
entity |
| Predicate | genderOfHost |
P39158
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [Parisian salon at Rue de Courcelles, genderOfHost, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderOfHost Context triple: [Parisian salon at Rue de Courcelles, genderOfHost, female]
-
A.
hasHostGender
chosen
Indicates that an entity has or is associated with a specific gender of its host.
-
B.
genderOfPersona
Indicates the gender identity associated with a given persona.
-
C.
genderOfTypicalHolder
Indicates the gender that is most commonly associated with or typical of the usual holder of something.
-
D.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
E.
genderCustom
Indicates that an entity has a user-specified or non-standard gender designation beyond predefined gender categories.
- 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_69e11e3a95d88190a3bd80d9471976c3 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129b9ee54819081141c4f28e1211a |
completed | April 28, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e71b384e008190b723c9a0f1089d66 |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:32 p.m.