Triple
T31229526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noose for a Gunman |
E796239
|
entity |
| Predicate | hasNarrativeLocationType |
P55822
|
FINISHED |
| Object | Western frontier 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: Western frontier town | Statement: [Noose for a Gunman, hasNarrativeLocationType, Western frontier town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNarrativeLocationType Context triple: [Noose for a Gunman, hasNarrativeLocationType, Western frontier town]
-
A.
narrativeLocationType
chosen
Indicates the type or role of a location within the structure or context of a narrative (e.g., setting, origin, destination).
-
B.
locationOfNarrative
Indicates the place or setting where the events or story described in the narrative occur.
-
C.
hasTypeInNarrative
Indicates that an entity is assigned a specific type or role within the context of a particular narrative.
-
D.
hasNarrativeContext
Indicates that an entity is associated with, or situated within, a particular narrative or storytelling context that frames its meaning or role.
-
E.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
- F. None of above.
Provenance (3 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_69f224da98f88190ab32f690cce5d303 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: April 29, 2026, 9:10 p.m.