Triple
T35001042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheriff Talbott |
E1009676
|
entity |
| Predicate | settingTypeOfWorkAppearedIn |
P193328
|
FINISHED |
| Object | small Southern town |
—
|
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: small Southern town | Statement: [Sheriff Talbott, settingTypeOfWorkAppearedIn, small Southern town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingTypeOfWorkAppearedIn Context triple: [Sheriff Talbott, settingTypeOfWorkAppearedIn, small Southern town]
-
A.
settingOfWorkAppearsIn
Indicates that a particular place, time, or environment serves as the setting within which a given creative work’s events or narrative occur.
-
B.
settingOfWorks
Indicates that a place or environment serves as the primary setting where the events or narratives of one or more works take place.
-
C.
settingOfWork
Indicates the place, time, or environment in which a creative work’s narrative or events are situated.
-
D.
introducedInWorkType
Indicates that an entity was first introduced or appeared in a work of a specified type (e.g., book, film, game).
-
E.
settingOfWorkFeaturedIn
Indicates that a place or environment serves as the primary setting where the events of a creative work take place.
- 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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
| PDg | Predicate description generation | batch_69fd4128ed908190837ec9936774a1cf |
completed | May 8, 2026, 1:49 a.m. |
Created at: May 3, 2026, 4:01 p.m.