Triple
T2292445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suez |
E51534
|
entity |
| Predicate | hasNearbyIndustrialZone |
P20649
|
FINISHED |
| Object | Suez industrial areas |
—
|
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: Suez industrial areas | Statement: [Suez, hasNearbyIndustrialZone, Suez industrial areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyIndustrialZone Context triple: [Suez, hasNearbyIndustrialZone, Suez industrial areas]
-
A.
hasNearbyIndustry
chosen
Indicates that an entity is located close to one or more industrial facilities or activities.
-
B.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
C.
isIndustrialCenter
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
-
D.
hasIndustrialPark
Indicates that a location or entity possesses or contains an industrial park within its area or jurisdiction.
-
E.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:48 p.m.