Triple
T13316559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harukas 300 |
E317201
|
entity |
| Predicate | hasTicketCounterLocation |
P60844
|
FINISHED |
| Object | 16th floor of Abeno Harukas |
—
|
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: 16th floor of Abeno Harukas | Statement: [Harukas 300, hasTicketCounterLocation, 16th floor of Abeno Harukas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTicketCounterLocation Context triple: [Harukas 300, hasTicketCounterLocation, 16th floor of Abeno Harukas]
-
A.
hasTicketGatesLocation
Indicates that a place or facility has ticket gates located at or within a specified location.
-
B.
hasTicketCollectorArea
Indicates that a location or facility includes a designated area where ticket collectors operate or perform their duties.
-
C.
hasTicketBooths
chosen
Indicates that one entity possesses or contains ticket booths used for selling or distributing tickets.
-
D.
hasTicketHall
Indicates that a place or facility includes or is equipped with a designated ticket hall area for purchasing or validating tickets.
-
E.
hasCheckInCounters
Indicates that an entity is associated with one or more check-in counters used for processing arrivals or registrations.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6babd88190a5d529df9584b9a4 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.