Triple
T14930766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acadia Parish |
E372255
|
entity |
| Predicate | parishSeatPopulationRankInParish |
P116709
|
FINISHED |
| Object | largest city |
—
|
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: largest city | Statement: [Acadia Parish, parishSeatPopulationRankInParish, largest city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parishSeatPopulationRankInParish Context triple: [Acadia Parish, parishSeatPopulationRankInParish, largest city]
-
A.
isParishSeatOf
Indicates that a location serves as the administrative center or main seat of government for a particular parish.
-
B.
hasPopulationRankInUK
Indicates the relative position of an entity’s population size compared to other entities within the United Kingdom.
-
C.
civilParishNumber
Indicates the identifying number assigned to a specific civil parish within an administrative or geographic system.
-
D.
boroughPopulation
Indicates the total number of people living within a specific borough.
-
E.
municipalityPopulation
Indicates the total number of inhabitants living within a given municipality.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64550dc8190ba44120df00ba498 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:36 a.m.