Triple
T31026797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ho Chi Minh City Metro |
E790599
|
entity |
| Predicate | hasPlannedLines |
P86666
|
FINISHED |
| Object | Line 1 |
—
|
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: Line 1 | Statement: [Ho Chi Minh City Metro, hasPlannedLines, Line 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedLines Context triple: [Ho Chi Minh City Metro, hasPlannedLines, Line 1]
-
A.
hasPlannedLine
chosen
Indicates that an entity is associated with a specific planned route or line intended for future or scheduled use.
-
B.
hasPlannedPart
Indicates that one entity includes another entity as a component or segment within a planned or scheduled whole.
-
C.
hasPlannedTrain
Indicates that an entity is associated with a train that is scheduled or planned to operate, rather than one currently in service.
-
D.
hasPlan
Indicates that an entity possesses or is associated with a specific plan or course of action.
-
E.
hasPlannedSectors
Indicates that an entity is associated with specific sectors that have been identified or designated in advance for future activity, development, or focus.
- 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_69f224c811508190a7de096a5b1f5798 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
Created at: April 29, 2026, 8:58 p.m.