Triple
T18927759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanisivik |
E463017
|
entity |
| Predicate | formerPopulationType |
P6347
|
FINISHED |
| Object | company town |
—
|
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: company town | Statement: [Nanisivik, formerPopulationType, company town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerPopulationType Context triple: [Nanisivik, formerPopulationType, company town]
-
A.
formerPopulation
Indicates that an entity once had a certain population value or size during a past time period but no longer does.
-
B.
hadPopulationType
chosen
Indicates that an entity possessed a particular classification or type of population during a given time or context.
-
C.
hasPopulationType
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
-
D.
servicePopulationType
Indicates the type or category of population that a service is intended to serve or target.
-
E.
populationClass
Indicates a categorical classification of a population based on shared characteristics, status, or demographic criteria.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c9bdddb481908bebd32f927ed5de |
completed | April 20, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69e4a2efec5c8190840704016bf547a1 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 11:59 a.m.