Triple
T1689447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitehall Terminal |
E36517
|
entity |
| Predicate | hasNumberOfFerrySlips |
P31355
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Whitehall Terminal, hasNumberOfFerrySlips, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfFerrySlips Context triple: [Whitehall Terminal, hasNumberOfFerrySlips, 3]
-
A.
hasFerryPort
Indicates that a place serves as a location where ferries regularly dock to load and unload passengers or cargo.
-
B.
hasFerryService
Indicates that there is an operational ferry connection or transport service available between the related locations or entities.
-
C.
hasBerths
Indicates that one entity provides or contains sleeping or docking berths for another entity.
-
D.
eraOfMajorUseAsFerryTerminal
Indicates the time period during which a location was primarily used as a ferry terminal.
-
E.
hasNearbyFerryPort
Indicates that one location is situated close enough to another location that serves as a ferry port to be considered nearby.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf3359ce48190803b322db8ad6027 |
completed | March 6, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69aa61b71cec8190b273588051058ebd |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aaf33347e48190a32b6d0099e3d389 |
completed | March 6, 2026, 3:30 p.m. |
Created at: March 4, 2026, 7:29 p.m.