Triple
T35589710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aliağa Municipality |
E1028459
|
entity |
| Predicate | sectoralContext |
P71
|
FINISHED |
| Object | heavy industry |
—
|
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: heavy industry | Statement: [Aliağa Municipality, sectoralContext, heavy industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectoralContext Context triple: [Aliağa Municipality, sectoralContext, heavy industry]
-
A.
sectoralExample
Indicates that something serves as a representative or illustrative example within a particular sector or industry context.
-
B.
sectoralEngagement
Indicates engagement or involvement between entities within a specific sector or industry context.
-
C.
sectoralCoverage
Indicates the specific sectors, industries, or domains to which something (such as a policy, agreement, or dataset) applies or extends.
-
D.
sector
chosen
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
E.
sectoralClassification
Indicates how an entity is categorized into a specific economic or industry sector within a classification scheme.
- 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_69f76e0495a081909beced418558c0b4 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.