Triple
T30880395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saigon River Tunnel |
E786592
|
entity |
| Predicate | hasFireProtectionSystem |
P25136
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Saigon River Tunnel, hasFireProtectionSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFireProtectionSystem Context triple: [Saigon River Tunnel, hasFireProtectionSystem, yes]
-
A.
hasFireExtinguishers
Indicates that the subject is equipped with or possesses one or more fire extinguishers.
-
B.
hasSprinklers
Indicates that an entity is equipped with or contains sprinkler systems.
-
C.
hasFireControlSystem
Indicates that an entity is equipped with or includes a fire control system used to detect, track, and direct weapons or suppression against targets.
-
D.
hasEmergencySystems
chosen
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
-
E.
usesSafetySystemsFrom
Indicates that one entity employs or relies on the safety systems that originate from or are provided by another entity.
- 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_69f224bae17c8190bb3a6a28e3d019df |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe30bc64308190b603ff1b30c2aeee |
completed | May 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fe2f7175b081908dd61e1513620bbe |
completed | May 8, 2026, 6:46 p.m. |
Created at: April 29, 2026, 8:48 p.m.