Triple
T33535611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridge City |
E858912
|
entity |
| Predicate | associatedWithRiverCityIdentity |
P95165
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Bridge City, associatedWithRiverCityIdentity, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithRiverCityIdentity Context triple: [Bridge City, associatedWithRiverCityIdentity, yes]
-
A.
associatedWithCityBranding
chosen
Indicates a relationship where something is connected to, involved in, or contributes to the branding or promotional identity of a city.
-
B.
associatedWithCityGroup
Indicates a relationship where an entity is linked or connected to a specific group or collection of cities.
-
C.
associatedWithSuperheroIdentity
Indicates that an entity has a connection or linkage to a particular superhero identity, such as being or representing that superhero persona.
-
D.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
E.
associatedWithCityFoundation
Indicates a relationship where an entity is connected to, involved in, or relevant to the founding or establishment of a particular city.
- 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_69f34978caf4819083f90eba4944d8e8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:39 a.m.