Triple
T33753349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Absaroka County, Wyoming |
E864903
|
entity |
| Predicate | hasNotableResidentCharacter |
P196490
|
FINISHED |
| Object | Walt Longmire |
E857361
|
NE 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: Walt Longmire | Statement: [Absaroka County, Wyoming, hasNotableResidentCharacter, Walt Longmire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableResidentCharacter Context triple: [Absaroka County, Wyoming, hasNotableResidentCharacter, Walt Longmire]
-
A.
hasNotableResident
Indicates that an entity is or has been a well-known or distinguished resident of a particular place or location.
-
B.
hasNotableResidentInFiction
chosen
Indicates that a place or entity is notably associated with a fictional character who is depicted as residing there.
-
C.
hasNotableResidentInTimeline
Indicates that an entity has, at some point in its historical timeline, a notable resident associated with it.
-
D.
notableInhabitantClass
Indicates that a place or location is known for being inhabited by a particular class or type of notable beings or entities.
-
E.
hasTypicalResident
Indicates that an entity characteristically or commonly has a particular type of resident associated with it.
- F. None of above.
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_69f3498c35f881909df279ae4270f831 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01ed1790148190b08c1dba53de4371 |
completed | May 11, 2026, 2:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a366e87bb8881909e8138c2f19d7caa |
completed | June 20, 2026, 10:42 a.m. |
| PD | Predicate disambiguation | batch_6a01e9c20798819085760b377dc7b3fa |
completed | May 11, 2026, 2:37 p.m. |
Created at: May 1, 2026, 1:45 a.m.