Triple
T9548504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collin Fenwick |
E230357
|
entity |
| Predicate | settingOfNarration |
P89733
|
FINISHED |
| Object | small Southern town (fictional) |
—
|
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 (fictional) | Statement: [Collin Fenwick, settingOfNarration, small Southern town (fictional)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfNarration Context triple: [Collin Fenwick, settingOfNarration, small Southern town (fictional)]
-
A.
hasNarration
Indicates that an entity provides spoken or written commentary or storytelling for another entity, such as a work, event, or scene.
-
B.
sectionNarrator
Indicates that a given entity serves as the narrator or narrative voice for a particular section of a work.
-
C.
narratorType
Indicates the narrative perspective or role from which a story or account is being told.
-
D.
narratorOf
Indicates that one entity serves as the narrator or storytelling voice for another entity, such as a text, story, or media work.
-
E.
narratedTo
Indicates that one entity tells or recounts a story, event, or information directly to another entity as the audience.
- 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99059138819088ae54b26df979cf |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:02 p.m.