Triple
T413887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transport for Greater Manchester |
E9548
|
entity |
| Predicate | numberOfLinesOperated |
P4876
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Transport for Greater Manchester, numberOfLinesOperated, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLinesOperated Context triple: [Transport for Greater Manchester, numberOfLinesOperated, 8]
-
A.
hasNumberOfLines
chosen
Indicates the relationship that specifies how many lines are associated with a given entity.
-
B.
operatedFor
Indicates that one entity performed operations or provided services on behalf of, or in support of, another entity for a certain period or purpose.
-
C.
operatesOver
Indicates that one entity performs actions or exerts functional control across, upon, or throughout another entity or domain.
-
D.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
E.
numberOfElementsCovered
Indicates the count of distinct elements that are included or encompassed by a given entity or condition.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecdd3d1c8190a31b071569cfc980 |
completed | Feb. 28, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69a2e9749234819084b0ce94faabd0b1 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.