Triple
T30475327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rex Hotel Saigon |
E775426
|
entity |
| Predicate | hasFormerCityNameContext |
P40182
|
FINISHED |
| Object | Saigon |
—
|
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: Saigon | Statement: [Rex Hotel Saigon, hasFormerCityNameContext, Saigon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerCityNameContext Context triple: [Rex Hotel Saigon, hasFormerCityNameContext, Saigon]
-
A.
hasAssociatedCityFormerName
chosen
Indicates that an entity is linked to a city by referencing one of that city's former or historical names.
-
B.
hasOldCity
Indicates that an entity possesses or contains an old or historic city as part of its domain or structure.
-
C.
formerCityContext
Indicates that the subject entity was formerly classified or recognized as a city within the specified contextual scope or time frame.
-
D.
hasPredecessorNameInCity
Indicates that an entity has a predecessor (e.g., an earlier version or prior holder) that had the same name in a specified city.
-
E.
isInFormerCapital
Indicates that an entity is located within a city that previously served as a capital but no longer holds that status.
- 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_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: April 29, 2026, 8:11 p.m.