Triple
T27052937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ho Chi Minh City – Con Dao |
E684824
|
entity |
| Predicate | departureAirportCity |
P90676
|
FINISHED |
| Object | Ho Chi Minh City |
—
|
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: Ho Chi Minh City | Statement: [Ho Chi Minh City – Con Dao, departureAirportCity, Ho Chi Minh City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: departureAirportCity Context triple: [Ho Chi Minh City – Con Dao, departureAirportCity, Ho Chi Minh City]
-
A.
destinationAirportCity2
Indicates the city of the airport that serves as the second (or alternative) destination in a travel or flight-related context.
-
B.
destinationCity
Indicates the city to which an entity is traveling, being sent, or ultimately directed.
-
C.
hasOriginAirportCity
chosen
Indicates that an entity (such as a flight or trip) departs from or is associated with a specific origin airport located in a given city.
-
D.
airportNameOrigin
Indicates the name of the airport that serves as the origin point in a trip or flight-related relationship.
-
E.
firstFlightCity
Indicates the city from which an entity’s first flight departs.
- 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_69ef14829fac8190914bef9ecc3005d7 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f622b145848190b67cfdc47da6a887 |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 8:15 a.m.