Triple
T36363976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaines Street in various U.S. cities |
E895569
|
entity |
| Predicate | hasTypicalInstance |
P200584
|
FINISHED |
| Object | Gaines Street (Tallahassee, Florida) |
—
|
NE NERFINISHED |
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: Gaines Street (Tallahassee, Florida) | Statement: [Gaines Street in various U.S. cities, hasTypicalInstance, Gaines Street (Tallahassee, Florida)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalInstance Context triple: [Gaines Street in various U.S. cities, hasTypicalInstance, Gaines Street (Tallahassee, Florida)]
-
A.
hasTypicalUsageType
Indicates that something is associated with a standard or commonly expected way in which it is used.
-
B.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
C.
hasTypicalBody
Indicates that an entity possesses the standard or characteristic physical form commonly associated with its kind or category.
-
D.
hasTypicalSequence
Indicates that there is a usual or commonly occurring order or progression in which the related entities or events take place.
-
E.
hasTypicalFiber
Indicates that an entity is characteristically associated with a particular type or kind of fiber.
- 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_69f76e5044248190b390d8887dc03254 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff97637ad881908c24fe2cc6b036db |
completed | May 9, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69ff96c43a808190942eeda1934602db |
completed | May 9, 2026, 8:19 p.m. |
| PDg | Predicate description generation | batch_69ff976281888190a2e872296fb4a661 |
completed | May 9, 2026, 8:21 p.m. |
Created at: May 3, 2026, 4:10 p.m.