Triple
T24881273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas–Fort Worth Spurs |
E622714
|
entity |
| Predicate | earlyProfessionalPresenceIn |
P157772
|
FINISHED |
| Object | Dallas–Fort Worth metropolitan area |
—
|
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: Dallas–Fort Worth metropolitan area | Statement: [Dallas–Fort Worth Spurs, earlyProfessionalPresenceIn, Dallas–Fort Worth metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earlyProfessionalPresenceIn Context triple: [Dallas–Fort Worth Spurs, earlyProfessionalPresenceIn, Dallas–Fort Worth metropolitan area]
-
A.
earlyCareerAt
Indicates that an entity spent the early part of its career working at or being affiliated with another entity.
-
B.
earlyPresence
Indicates that one entity is present or arrives earlier than another reference point, event, or entity.
-
C.
earlyCareerActivity
Indicates activities, roles, or engagements undertaken by an entity during the early stage of its career or professional development.
-
D.
earlyCareerCoach
Indicates that one entity serves as a coach or mentor to another during the early stage of that other entity’s career.
-
E.
earlyTraining
Indicates that an entity receives or provides training at an early stage relative to a process, development period, or typical timeline.
- 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_69e2fac4aa848190b3446a3922cec150 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442b8479c8190a7c8e416ac9e28a0 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f44a3adb7c8190941572f718b3b93c |
completed | May 1, 2026, 6:37 a.m. |
Created at: April 18, 2026, 5:24 a.m.