Triple

T35554443
Position Surface form Disambiguated ID Type / Status
Subject Green’s Bluff E1027452 entity
Predicate hasSuccessorCity P109588 FINISHED
Object Orange, 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: Orange, Texas | Statement: [Green’s Bluff, hasSuccessorCity, Orange, Texas]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSuccessorCity
Context triple: [Green’s Bluff, hasSuccessorCity, Orange, Texas]
  • A. hasCitySuccessor chosen
    Indicates that one city is the successor or replacement of another city, typically in terms of status, function, or administrative role.
  • B. coordinateLocationOfSuccessorCity
    Indicates that the coordinates specified correspond to the geographic location of a city that has succeeded or replaced another city.
  • C. successorInCity
    Indicates that one entity directly follows or replaces another in holding a particular role, position, or function within the same city.
  • D. hasCityServedSuccessor
    Indicates that one city served by a service, role, or entity is the successor to another previously served city in that same context.
  • E. followedByCity
    Indicates that one city comes immediately after another in a specified sequence, order, or path.
  • 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_69f76e014fd481909e9f04ac603a2aa9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69ffe23081408190a121d901dbce1403 completed May 10, 2026, 1:41 a.m.
PD Predicate disambiguation batch_69ffe18aed348190912a5996b2da728b completed May 10, 2026, 1:38 a.m.
Created at: May 3, 2026, 4:04 p.m.