Triple
T32527324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jon Voight as Lord Richard Croft |
E831349
|
entity |
| Predicate | realLifeRelationshipWithLaraCroftActress |
P174909
|
FINISHED |
| Object | father |
—
|
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: father | Statement: [Jon Voight as Lord Richard Croft, realLifeRelationshipWithLaraCroftActress, father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realLifeRelationshipWithLaraCroftActress Context triple: [Jon Voight as Lord Richard Croft, realLifeRelationshipWithLaraCroftActress, father]
-
A.
realLifeRelationshipWithAngelinaJolie
Indicates that there exists a real-life personal relationship or connection between the subject and Angelina Jolie.
-
B.
relationshipToJodieHolmes
Indicates the nature or type of relationship an entity has with Jodie Holmes.
-
C.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
D.
relationshipWithMelinaVostokoff
Indicates a relationship or connection that an entity has with Melina Vostokoff.
-
E.
relationshipToNicole
Indicates the specific type of relationship or connection that an entity has with Nicole.
- 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_69f34923e1548190be0524205d8cdf8f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c90790788190a1ed09adc86ed22d |
completed | May 3, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c814c26c81908f5c47285129ff2a |
completed | May 3, 2026, 3:59 a.m. |
Created at: May 1, 2026, 1:01 a.m.