Triple
T37622580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libby Tucker |
E936109
|
entity |
| Predicate | relationshipToHerb Tucker |
P108596
|
FINISHED |
| Object | daughter |
—
|
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: daughter | Statement: [Libby Tucker, relationshipToHerb Tucker, daughter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToHerb Tucker Context triple: [Libby Tucker, relationshipToHerb Tucker, daughter]
-
A.
relationshipToTucker
chosen
Indicates the specific familial, social, or professional relationship that one entity has to Tucker.
-
B.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
C.
relationshipToTina
Indicates the specific type of personal or social relationship that an entity has with Tina.
-
D.
relationshipTypeWithTaylorTravis
Indicates the specific nature or category of the relationship that an entity has with Taylor Travis.
-
E.
relationshipTypeWithJackieTaylor
Indicates the specific type or nature of the relationship that an entity has with Jackie Taylor.
- F. None of above.
Provenance (3 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_69f76ed16b748190ad6add183b1be688 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:18 p.m.