Triple
T33108810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hat Yao Pier |
E847268
|
entity |
| Predicate | servesTypeOfTraveler |
P27830
|
FINISHED |
| Object | domestic tourists |
—
|
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: domestic tourists | Statement: [Hat Yao Pier, servesTypeOfTraveler, domestic tourists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesTypeOfTraveler Context triple: [Hat Yao Pier, servesTypeOfTraveler, domestic tourists]
-
A.
servesTravelersTo
Indicates a relationship where one entity provides services, assistance, or accommodations specifically directed toward travelers heading to a particular destination.
-
B.
servesBusinessTravel
Indicates that an entity provides services or accommodations specifically intended for business-related travel.
-
C.
offersClassOfTravel
Indicates that a service provider makes a particular class or tier of travel (e.g., economy, business, first) available as an option.
-
D.
servesPassengerTrafficType
chosen
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
-
E.
servedTravelersBetween
Indicates that an entity provided transportation service for travelers moving between two specified locations.
- 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_69f3495686508190b76bf20fa5e00bf7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff519b65f081909902ba83b775ef85 |
completed | May 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69ff506fccdc8190bd93269589040aed |
completed | May 9, 2026, 3:19 p.m. |
Created at: May 1, 2026, 1:27 a.m.