Triple
T31585403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Beach FlyAway stop |
E805942
|
entity |
| Predicate | hasServiceFrom |
P199107
|
FINISHED |
| Object | Los Angeles International Airport |
—
|
NE NERFINISHED |
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: Los Angeles International Airport | Statement: [Long Beach FlyAway stop, hasServiceFrom, Los Angeles International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceFrom Context triple: [Long Beach FlyAway stop, hasServiceFrom, Los Angeles International Airport]
-
A.
hasServiceTo
Indicates that one entity provides, offers, or operates a service for or directed toward another entity.
-
B.
hasThroughServiceWith
Indicates that two transportation services are operationally linked so that a passenger or shipment can continue from one to the other without a separate booking or major interruption.
-
C.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
D.
hasSupportService
Indicates that one entity provides or is associated with a support-related service for another entity.
-
E.
hasConstituentServicesIn
Indicates that an entity provides constituent services within a specified geographic or jurisdictional area.
- 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_69f348d4891c8190b02bae3c8ecb68b7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff1f3f94fc819095955299f50ab4ce |
completed | May 9, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69ff1ea47748819082f63d9b9d9c3e65 |
completed | May 9, 2026, 11:46 a.m. |
| PDg | Predicate description generation | batch_69ff1f3ee3588190a857d1504c93be8b |
completed | May 9, 2026, 11:49 a.m. |
Created at: April 30, 2026, 10:25 p.m.