Triple
T38574698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perai, Penang |
E929367
|
entity |
| Predicate | hasPortFacilityNearby |
P86796
|
FINISHED |
| Object | North Butterworth Container Terminal |
—
|
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: North Butterworth Container Terminal | Statement: [Perai, Penang, hasPortFacilityNearby, North Butterworth Container Terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortFacilityNearby Context triple: [Perai, Penang, hasPortFacilityNearby, North Butterworth Container Terminal]
-
A.
nearbyPortFacility
chosen
Indicates that one entity is located close to or in the immediate vicinity of a port facility.
-
B.
hasNearbyFerryPort
Indicates that one location is situated close enough to another location that serves as a ferry port to be considered nearby.
-
C.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
D.
hasNearbyPortAccess
Indicates that an entity is located close enough to a port to feasibly use it for access or transport.
-
E.
hasNearbyPier
Indicates that one entity is located close to a pier associated with or adjacent to another entity.
- 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_69f76ebd2248819083978362d81fa35e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a0018cf6ebc8190aee6288788d0067e |
completed | May 10, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_6a001855e8588190a65840485473cf8b |
completed | May 10, 2026, 5:32 a.m. |
Created at: May 3, 2026, 4:32 p.m.