Triple
T27014391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodrow F. Call |
E680484
|
entity |
| Predicate | relationshipToNewtDobbs |
P199364
|
FINISHED |
| Object | biological 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: biological father | Statement: [Woodrow F. Call, relationshipToNewtDobbs, biological father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToNewtDobbs Context triple: [Woodrow F. Call, relationshipToNewtDobbs, biological father]
-
A.
hasRelationshipTypeWith Frank Drebin
Indicates that there exists a specific type of relationship between an entity and Frank Drebin.
-
B.
relationshipToBobinot
Indicates the nature or type of relationship that one entity has with Bobinot.
-
C.
relationshipToNevilleFlynn
Indicates a specified type of personal or social relationship that an entity has with Neville Flynn.
-
D.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
-
E.
relationshipToDeloris
Indicates the specific type of personal, familial, or social relationship that one entity has with the entity named Deloris.
- 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69ff32b88bf48190b45afd1b60cb511c |
completed | May 9, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69ff3031e18881908927b2ab452de863 |
completed | May 9, 2026, 1:01 p.m. |
| PDg | Predicate description generation | batch_69ff32b6dd448190a7a6ebb76b99d4cc |
completed | May 9, 2026, 1:12 p.m. |
Created at: April 27, 2026, 7:05 a.m.