Triple
T24700447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corinth, Texas |
E611720
|
entity |
| Predicate | proximityToUrbanCenter |
P36605
|
FINISHED |
| Object | Fort Worth, Texas |
—
|
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: Fort Worth, Texas | Statement: [Corinth, Texas, proximityToUrbanCenter, Fort Worth, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proximityToUrbanCenter Context triple: [Corinth, Texas, proximityToUrbanCenter, Fort Worth, Texas]
-
A.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
-
B.
connectsToUrbanCenter
Indicates that one entity has a direct or functional linkage to an urban center, such as through infrastructure, services, or regular interaction.
-
C.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
isFartherFromCityCenterThan
Indicates that one location is at a greater distance from the city center than another location.
-
E.
distanceFromMajorPopulationCenters
Indicates the physical distance between a location and the nearest major population centers.
- 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_69e2c4d76d148190b58ad612467149a5 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 3:22 a.m.