Triple
T33374290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Ashley |
E854581
|
entity |
| Predicate | relationshipWithPhilipAshley |
P206436
|
FINISHED |
| Object | cousin by marriage |
—
|
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: cousin by marriage | Statement: [Rachel Ashley, relationshipWithPhilipAshley, cousin by marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithPhilipAshley Context triple: [Rachel Ashley, relationshipWithPhilipAshley, cousin by marriage]
-
A.
relationshipTypeWithPhilipTempest
Indicates the specific nature or category of relationship an entity has with Philip Tempest.
-
B.
relationshipToPhilipMarlow
Indicates the specific type of personal or social relationship an entity has to Philip Marlow.
-
C.
hasRelationshipTypeWith Philippe Renaldo
Indicates that there exists a specific type or category of relationship between an entity and Philippe Renaldo.
-
D.
hasRelationshipTypeWith Tai Frasier
Indicates that there exists a specific type of relationship between an entity and Tai Frasier.
-
E.
relationshipTypeWithHayleyTravis
Indicates the specific nature or category of the relationship that an entity has with Hayley Travis.
- 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_69f3496ca10c8190908640d18fa00832 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:35 a.m.