Triple
T5927054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalloni |
E131837
|
entity |
| Predicate | hasBayType |
P45093
|
FINISHED |
| Object | semi-enclosed bay |
—
|
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: semi-enclosed bay | Statement: [Kalloni, hasBayType, semi-enclosed bay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBayType Context triple: [Kalloni, hasBayType, semi-enclosed bay]
-
A.
hasBayPlatforms
Indicates that a station or terminal is equipped with bay platforms, where tracks end in a dead-end configuration and trains enter and exit from the same direction.
-
B.
hasNotableBay
Indicates that a place possesses a bay that is recognized for its significance, prominence, or special interest.
-
C.
bayType
chosen
Indicates the specific kind or classification of a bay associated with an entity.
-
D.
hasBusBays
Indicates that a location or facility is equipped with one or more designated bus bays for buses to stop, load, or unload passengers.
-
E.
hasBenchType
Indicates that an entity is associated with or characterized by a specific type or category of bench.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.