Triple
T3099220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laban |
E64673
|
entity |
| Predicate | hasDaughterInLawRelation |
P31445
|
FINISHED |
| Object | Jacob as son-in-law |
—
|
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: Jacob as son-in-law | Statement: [Laban, hasDaughterInLawRelation, Jacob as son-in-law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDaughterInLawRelation Context triple: [Laban, hasDaughterInLawRelation, Jacob as son-in-law]
-
A.
sonInLaw
chosen
Indicates that one person is the husband of another person's child.
-
B.
hasNotableDaughter
Indicates that an entity has at least one daughter who is notable or significant in some recognized way.
-
C.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
D.
marriedIn
Indicates that two entities entered into a marital relationship at a specific place or within a particular jurisdiction.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada269a9188190aada5b3799d4dfd7 |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df06ed88190809f0683122caa5a |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:03 p.m.