Triple
T23493094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eskişehir light rail system |
E571628
|
entity |
| Predicate | hasLines |
P152594
|
FINISHED |
| Object | multiple lines |
—
|
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: multiple lines | Statement: [Eskişehir light rail system, hasLines, multiple lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLines Context triple: [Eskişehir light rail system, hasLines, multiple lines]
-
A.
hasNumberOfLines
Indicates the relationship that specifies how many lines are associated with a given entity.
-
B.
hasLineStructure
Indicates that one entity possesses or exhibits a linear arrangement or organization of its components.
-
C.
hasFastLines
Indicates that the subject possesses or is associated with lines that operate or move at a high speed.
-
D.
hasLineCharacter
Indicates that one entity possesses or includes a specific character or symbol that appears within a line of text or sequence.
-
E.
hasLineSection
Indicates that an entity includes, contains, or is composed of a specific segment or section of a line.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7dd56408190b459077e433ed1c3 |
completed | April 29, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:05 p.m.