Triple
T37625998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Road 50 |
E936209
|
entity |
| Predicate | hasLocalNameInOrlando |
P200698
|
FINISHED |
| Object | West Colonial Drive |
—
|
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: West Colonial Drive | Statement: [State Road 50, hasLocalNameInOrlando, West Colonial Drive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalNameInOrlando Context triple: [State Road 50, hasLocalNameInOrlando, West Colonial Drive]
-
A.
hasMetropolitanAreaName
Indicates that an entity is associated with a metropolitan area identified by a specific name.
-
B.
isLocalOn
Indicates that something resides or operates on a specific local device, system, or node rather than remotely.
-
C.
isLocatedAtAirportServingCity
Indicates that something is situated at an airport that provides service to a particular city.
-
D.
isSpaTownOf
Indicates that a place is recognized as a spa town belonging to, or located within the jurisdiction of, a specified larger administrative area or region.
-
E.
homeCityForMiami
Indicates that the subject city serves as the home city (primary or base city) for Miami in the specified relationship or context.
- 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_69f76ed24820819081bafd36e9088701 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffa15d53208190ab8574d6c7913e18 |
completed | May 9, 2026, 9:04 p.m. |
| PD | Predicate disambiguation | batch_69ff9eee681c81909434e79c627cb528 |
completed | May 9, 2026, 8:54 p.m. |
| PDg | Predicate description generation | batch_69ffa15c3f348190a59403bc72ac9ed4 |
completed | May 9, 2026, 9:04 p.m. |
Created at: May 3, 2026, 4:18 p.m.