Triple
T7273913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 2 (Dublin Airport) |
E162975
|
entity |
| Predicate | hasBoardingPier |
P15921
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Terminal 2 (Dublin Airport), hasBoardingPier, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardingPier Context triple: [Terminal 2 (Dublin Airport), hasBoardingPier, yes]
-
A.
hasPier
chosen
Indicates that a location or structure possesses or includes a pier as part of its features.
-
B.
hasFerryPort
Indicates that a place serves as a location where ferries regularly dock to load and unload passengers or cargo.
-
C.
hasHarbourEntrance
Indicates that an entity serves as the entrance or access point to a harbour for another entity.
-
D.
isHomePortOf
Indicates that a particular location serves as the primary base or port where a vessel or fleet is officially registered, stationed, or regularly returns.
-
E.
hasNearbyHarbor
Indicates that one location has a harbor situated close to it in geographic proximity.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb8a0b4881908ff27c5a75bd4a95 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76a84a081908d4184c55b728e48 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:58 p.m.