Triple
T8420149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Tanjung Pelepas |
E198827
|
entity |
| Predicate | numberOfBerths |
P82090
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Port of Tanjung Pelepas, numberOfBerths, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBerths Context triple: [Port of Tanjung Pelepas, numberOfBerths, 14]
-
A.
hasBerths
Indicates that one entity provides or contains sleeping or docking berths for another entity.
-
B.
wildCardBerthsCount
Indicates the number of wildcard berths (extra or non-standard qualification spots) allocated in a competition or selection process.
-
C.
berthType
Indicates the specific kind or category of berth associated with an entity, such as the type of sleeping or docking space provided.
-
D.
numberOfBays
Indicates the count of distinct bays associated with or contained within a given entity.
-
E.
hasNumberOfFerrySlips
Indicates the specific count of ferry slips associated with or available at a given entity.
- F. None of above. chosen
Provenance (4 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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb84c941988190884a5c0cbb44bcc2 |
completed | March 31, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb77690720819099de1e22b84a9563 |
completed | March 31, 2026, 7:27 a.m. |
Created at: March 30, 2026, 6:06 p.m.