Triple
T26180730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | municipal council of Maurepas |
E654671
|
entity |
| Predicate | sectoralCompetence |
P18508
|
FINISHED |
| Object | local roads and infrastructure |
—
|
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: local roads and infrastructure | Statement: [municipal council of Maurepas, sectoralCompetence, local roads and infrastructure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectoralCompetence Context triple: [municipal council of Maurepas, sectoralCompetence, local roads and infrastructure]
-
A.
competenceArea
chosen
Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
-
B.
sectoralCoverage
Indicates the specific sectors, industries, or domains to which something (such as a policy, agreement, or dataset) applies or extends.
-
C.
sectoralEngagement
Indicates engagement or involvement between entities within a specific sector or industry context.
-
D.
concurrentCompetenceArea
Indicates that two or more competence areas are active or applicable at the same time in relation to the same context, task, or entity.
-
E.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 26, 2026, 8:39 p.m.