Triple
T25886698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maw Maw |
E652206
|
entity |
| Predicate | relationshipToBurtChance |
P193873
|
FINISHED |
| Object | grandmother-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: grandmother-in-law | Statement: [Maw Maw, relationshipToBurtChance, grandmother-in-law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToBurtChance Context triple: [Maw Maw, relationshipToBurtChance, grandmother-in-law]
-
A.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
-
B.
relationshipToPete
Indicates the specific type of relationship or connection that an entity has to Pete.
-
C.
relationshipToAlBundy
Indicates the specific familial, social, or personal relationship that an entity has to the person Al Bundy.
-
D.
relationshipToTheDude
Indicates the specific type of personal or social relationship that one entity has to the individual referred to as "the Dude."
-
E.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
- 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_69e7ab3b92cc81908febd90317862647 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
| PDg | Predicate description generation | batch_69fd592cc56081908ce456114d407616 |
completed | May 8, 2026, 3:31 a.m. |
Created at: April 22, 2026, 8:18 a.m.