Triple
T28426800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cut Off, Louisiana |
E720102
|
entity |
| Predicate | parishSeatDistance |
P164715
|
FINISHED |
| Object | approximately 35 miles south of Thibodaux |
—
|
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: approximately 35 miles south of Thibodaux | Statement: [Cut Off, Louisiana, parishSeatDistance, approximately 35 miles south of Thibodaux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parishSeatDistance Context triple: [Cut Off, Louisiana, parishSeatDistance, approximately 35 miles south of Thibodaux]
-
A.
districtHeadquartersDistance
Indicates the distance between a place and its corresponding district headquarters.
-
B.
isParishSeatOf
Indicates that a location serves as the administrative center or main seat of government for a particular parish.
-
C.
municipalityCenterDistance
Indicates the distance between an entity and the central point of its corresponding municipality.
-
D.
roadDistanceToCityCentre_km
Indicates the distance in kilometers from a location to the city centre when traveling by road.
-
E.
nearParish
Indicates that one entity is geographically close to or in the vicinity of a specified parish.
- 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_69eff6f1c5088190bc24bfbf92f9c017 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64ee0c2788190a94a04ad1902fd5e |
completed | May 2, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f64e36c57c8190af09470a8d35512b |
completed | May 2, 2026, 7:19 p.m. |
Created at: April 28, 2026, 1:37 a.m.