Triple
T14702784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darling |
E345347
|
entity |
| Predicate | relationshipToTramp |
P115416
|
FINISHED |
| Object | owner |
—
|
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: owner | Statement: [Darling, relationshipToTramp, owner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToTramp Context triple: [Darling, relationshipToTramp, owner]
-
A.
relationshipToCarmen
Indicates the specific type of personal or social relationship an entity has with Carmen.
-
B.
relationshipToTracyLord
Indicates the specific type of personal or social relationship an entity has with Tracy Lord.
-
C.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
D.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
E.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb6071e5c8190bb5509c859135c2d |
completed | April 14, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716d3aac8190aaa6dc1f099b86e8 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:28 a.m.