Triple
T29837395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vallarpadam International Container Transshipment Terminal |
E757690
|
entity |
| Predicate | berthLength |
P123373
|
FINISHED |
| Object | around 600 metres |
—
|
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: around 600 metres | Statement: [Vallarpadam International Container Transshipment Terminal, berthLength, around 600 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: berthLength Context triple: [Vallarpadam International Container Transshipment Terminal, berthLength, around 600 metres]
-
A.
hasBerthLength
chosen
Indicates the length of a berth allocated to or associated with an entity.
-
B.
shipLength
Indicates the physical length measurement of a ship.
-
C.
hasBerthDepth
Indicates the depth of water available at a specific berth where a vessel can be moored.
-
D.
berthType
Indicates the specific kind or category of berth associated with an entity, such as the type of sleeping or docking space provided.
-
E.
hullLength_m
Indicates the length of an object's hull measured in meters.
- 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_69f224593f6c81908785a560fe659f58 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6760709588190affa39e86d0322f0 |
completed | May 2, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:37 p.m.