Triple
T19575069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum District station |
E489832
|
entity |
| Predicate | lineLengthType |
P136327
|
FINISHED |
| Object | urban light rail |
—
|
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: urban light rail | Statement: [Museum District station, lineLengthType, urban light rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineLengthType Context triple: [Museum District station, lineLengthType, urban light rail]
-
A.
hasLineLength
Indicates that one entity has, is characterized by, or is associated with a specific line length value.
-
B.
lineType
Indicates the specific category or style of a line used in a representation, such as its function or visual convention.
-
C.
laneLength
Indicates the length or distance of a lane in a given context.
-
D.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
E.
lineFamily
Indicates that two entities belong to the same family or lineage associated with a particular line (e.g., a family line or line-based grouping).
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e64023fe148190900c6887896c8ea0 |
completed | April 20, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
| PDg | Predicate description generation | batch_69e5174b060c81908937ff9ff7fce611 |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 1:42 p.m.