Triple
T9185965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liz |
E220458
|
entity |
| Predicate | isFeminineName |
P52140
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Liz, isFeminineName, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFeminineName Context triple: [Liz, isFeminineName, true]
-
A.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
B.
genderOfEponym
Indicates the gender of the person after whom something (such as a place, object, or concept) is named.
-
C.
hasFeminineFormInSomeLanguages
chosen
Indicates that the referenced entity has a distinct feminine grammatical or lexical form in at least one language.
-
D.
hasFemaleFormOf
Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
-
E.
genderSignificance
Indicates the relevance or impact that an entity’s gender has within a particular context, relationship, or interpretation.
- 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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc31a52508190a83ccd76f3aa039b |
completed | April 1, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69cc66090e5881908889dc1213815626 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:24 p.m.