Triple
T30475679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thu Dau Mot |
E775435
|
entity |
| Predicate | hasNearbyIndustrialZones |
P20649
|
FINISHED |
| Object | VSIP Binh Duong |
—
|
NE NERFINISHED |
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: VSIP Binh Duong | Statement: [Thu Dau Mot, hasNearbyIndustrialZones, VSIP Binh Duong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyIndustrialZones Context triple: [Thu Dau Mot, hasNearbyIndustrialZones, VSIP Binh Duong]
-
A.
hasIndustrialZoneAlong
Indicates that an industrial zone is located adjacent to or extending along the length of a specified linear feature (such as a road, river, or boundary).
-
B.
hasNearbyProductionArea
Indicates that one entity has a production area located in close physical proximity to it.
-
C.
adjacentToIndustrialArea
Indicates that one entity is located directly next to or bordering an industrial area.
-
D.
connectsToIndustrialArea
Indicates that one entity has a direct link, route, or access connection to an industrial area.
-
E.
hasNearbyIndustry
chosen
Indicates that an entity is located close to one or more industrial facilities or activities.
- 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_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69feabcda59481908f2bc13b46fcced1 |
completed | May 9, 2026, 3:36 a.m. |
| PD | Predicate disambiguation | batch_69feaabd63f88190b30dcf6dd2ea39d1 |
completed | May 9, 2026, 3:32 a.m. |
Created at: April 29, 2026, 8:11 p.m.