Triple
T8902830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echo and Narcissus |
E211969
|
entity |
| Predicate | depictsGenderOfEcho |
P27006
|
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: [Echo and Narcissus, depictsGenderOfEcho, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsGenderOfEcho Context triple: [Echo and Narcissus, depictsGenderOfEcho, female]
-
A.
playsGender
Indicates that one entity performs or assumes a particular gender role or identity in a given context.
-
B.
hasGenderInterpretation
Indicates that an entity is associated with a particular interpretation or understanding of gender.
-
C.
echoedIn
Indicates that a sound, statement, or effect produced in one context is repeated, reflected, or resonated in another context.
-
D.
genderPersonification
chosen
Indicates that a non-human entity is represented or treated as having a specific gender.
-
E.
genderTarget
Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
- 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_69ca83918d3081909b326fa3750cb8c8 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc64c091d08190b59e54eb4a184e41 |
completed | April 1, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69cc5ecf55248190a29f00fbf99f13c4 |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:55 p.m.