Triple
T18562542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha Hennessy |
E453680
|
entity |
| Predicate | publiclyIdentifiesAs |
P132502
|
FINISHED |
| Object | Catholic pacifist |
—
|
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: Catholic pacifist | Statement: [Martha Hennessy, publiclyIdentifiesAs, Catholic pacifist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publiclyIdentifiesAs Context triple: [Martha Hennessy, publiclyIdentifiesAs, Catholic pacifist]
-
A.
hasGenderIdentity
Indicates that an entity identifies with or experiences a particular gender.
-
B.
genderIdentityInSources
Indicates that the gender identity of an entity is recorded or referenced in one or more information sources.
-
C.
genderVariant
Indicates that an entity’s gender identity or expression differs from traditional or expected norms associated with their assigned sex or gender.
-
D.
protagonistGenderIdentity
Indicates the gender identity attributed to or expressed by the protagonist in a given context.
-
E.
isTraditionallyIdentifiedAs
Indicates that one entity is customarily or historically recognized or labeled as being the same as, or corresponding to, another entity.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53afb4f088190adf0b2b64057a210 |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:42 a.m.