Triple
T15836412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expo/Western station |
E383995
|
entity |
| Predicate | formerLineColor |
P119839
|
FINISHED |
| Object | Expo Line aqua |
—
|
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: Expo Line aqua | Statement: [Expo/Western station, formerLineColor, Expo Line aqua]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerLineColor Context triple: [Expo/Western station, formerLineColor, Expo Line aqua]
-
A.
formerColor
Indicates that an entity previously had a certain color, but no longer has that color now.
-
B.
formerLine
Indicates that an entity previously served as a particular transit or service line but no longer does so.
-
C.
formerColorScheme
Indicates that an entity previously used a particular color scheme but no longer does so.
-
D.
formerLineLetter
Indicates that one entity is a letter that previously belonged to a particular line (such as a transit line or route) but no longer does.
-
E.
formerLineName
Indicates that the object is a previous or former name by which the referenced line was known.
- F. None of above. chosen
Provenance (4 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e1fcd48190bcb884f6c65db847 |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e007647f908190adb178c68c7bb7cf |
completed | April 15, 2026, 9:47 p.m. |
Created at: April 10, 2026, 4:49 a.m.