Triple
T6911639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Census-designated place |
E159947
|
entity |
| Predicate | physicallyResembles |
P35666
|
FINISHED |
| Object | incorporated place |
—
|
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: incorporated place | Statement: [Census-designated place, physicallyResembles, incorporated place]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: physicallyResembles Context triple: [Census-designated place, physicallyResembles, incorporated place]
-
A.
resembles
chosen
Indicates that one entity is similar in appearance, form, or characteristics to another.
-
B.
materiallySimilarTo
Indicates that two entities share substantially the same physical or material characteristics, composition, or properties, though they may not be exactly identical.
-
C.
hasPhysicalFeature
Indicates that one entity possesses or exhibits a specific physical characteristic or feature of another entity.
-
D.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
E.
physicalCharacteristics
Indicates that one entity has or describes the bodily or material attributes, features, or appearance of another entity.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9c135b48190b332aedf1d52bdb7 |
completed | March 27, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:25 p.m.