Triple
T3313432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcoutim |
E69625
|
entity |
| Predicate | populationOfSeat |
P38055
|
FINISHED |
| Object | approximately 500 inhabitants |
—
|
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 500 inhabitants | Statement: [Alcoutim, populationOfSeat, approximately 500 inhabitants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationOfSeat Context triple: [Alcoutim, populationOfSeat, approximately 500 inhabitants]
-
A.
cityAsSeatOfGovernment
Indicates that a city serves as the official seat or location of a government’s central authority or administration.
-
B.
municipalitySeat
Indicates that one entity serves as the administrative center or capital (seat) of a municipality.
-
C.
municipalityPopulation
chosen
Indicates the total number of inhabitants living within a given municipality.
-
D.
mainSeatOf
Indicates that one entity serves as the primary or central seat (e.g., of government, administration, or authority) for another entity.
-
E.
cityPopulationContext
Indicates the contextual relationship between a city and information about its population, such as size, distribution, or demographic characteristics.
- 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_69ad85a0bb048190a5458d2738012d61 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0ef548481908b3aabc7052c70d8 |
completed | March 8, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69ada4282730819092aa39c5f9269df0 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.