Triple
T15905128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Jeffrey Squires |
E385691
|
entity |
| Predicate | relationshipToKristinSquires |
P120996
|
FINISHED |
| Object | husband |
—
|
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: husband | Statement: [Dr. Jeffrey Squires, relationshipToKristinSquires, husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToKristinSquires Context triple: [Dr. Jeffrey Squires, relationshipToKristinSquires, husband]
-
A.
relationshipStatusWithKrista
Indicates the current nature or state of an entity’s relationship with Krista.
-
B.
relationshipToJoannaKramer
Indicates the specific familial, social, or interpersonal connection that one entity has to Joanna Kramer.
-
C.
relationshipToKateKeller
Indicates the specific familial, social, or interpersonal connection that one entity has to Kate Keller.
-
D.
relationshipToChrisKeller
Indicates the specific type of personal or social relationship an entity has with Chris Keller.
-
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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:52 a.m.