Triple
T15664392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darl Bundren |
E377149
|
entity |
| Predicate | relationshipToAnseBundren |
P119665
|
FINISHED |
| Object | son |
—
|
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: son | Statement: [Darl Bundren, relationshipToAnseBundren, son]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAnseBundren Context triple: [Darl Bundren, relationshipToAnseBundren, son]
-
A.
relationshipToAlBundy
Indicates the specific familial, social, or personal relationship that an entity has to the person Al Bundy.
-
B.
relatedMemorial
Indicates a relationship where one entity serves as a memorial or commemorative reference to another entity.
-
C.
relationshipToCarolineCompson
Indicates the specific familial or social relationship that an entity has to Caroline Compson.
-
D.
associatedCemetery
Indicates that there is a relationship linking an entity (such as a person, event, or organization) to a specific cemetery with which it is connected.
-
E.
relationshipToMissWatson
Indicates the type or nature of a person's relational connection to Miss Watson (e.g., familial, social, or other defined relationship).
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f0f4df08190ad2c5d78e435d8eb |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:16 a.m.