Triple
T5452353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greater Austin metropolitan area |
E122397
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Leander, Texas |
E597864
|
NE 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: Leander, Texas | Statement: [Greater Austin metropolitan area, includesCity, Leander, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leander, Texas Context triple: [Greater Austin metropolitan area, includesCity, Leander, Texas]
-
A.
Leander, Texas
chosen
Leander, Texas is a rapidly growing suburban city in Central Texas that is part of the Greater Austin metropolitan area.
-
B.
Leo, Texas
Leo, Texas is a small rural unincorporated community located in Cooke County in north-central Texas.
-
C.
Leonard, Texas
Leonard, Texas is a small rural city in North Texas known for its tight-knit community and annual Leonard Picnic celebration.
-
D.
Navasota, Texas
Navasota, Texas is a small city in Grimes County that serves as a historic railroad and commercial hub within the Greater Houston metropolitan area.
-
E.
Lucas, Texas
Lucas, Texas is a small suburban city in North Texas known for its rural character, large residential lots, and location within the Dallas–Fort Worth metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd91dfec248190af6f9c793a99c34c |
completed | March 20, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c74208348c819080d1b4432ff617c0 |
completed | March 28, 2026, 2:50 a.m. |
Created at: March 20, 2026, 2:08 p.m.