Triple
T11935437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Industrial Area |
E284027
|
entity |
| Predicate | hasTypeOfOccupier |
P21135
|
FINISHED |
| Object | small and medium-sized enterprises |
—
|
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: small and medium-sized enterprises | Statement: [Southern Industrial Area, hasTypeOfOccupier, small and medium-sized enterprises]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfOccupier Context triple: [Southern Industrial Area, hasTypeOfOccupier, small and medium-sized enterprises]
-
A.
fieldOfOccupant
Indicates the specific professional or academic field in which an occupant is engaged or associated.
-
B.
occupiedBy
Indicates that a space, position, or role is currently being used, held, or filled by a particular entity.
-
C.
jurisdictionOfOccupant
Indicates the legal authority or control that an occupant exercises over a place, property, or domain.
-
D.
hasPrimaryOccupants
chosen
Indicates that certain entities are the main or principal occupants of another entity (such as a space, structure, or location).
-
E.
hasRelativeOccupation
Indicates that two people are related in such a way that one’s occupation is defined or characterized in relation to the other’s occupation.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90306fcf48190a963d2d1932288d1 |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.