Triple
T3416939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hop |
E72030
|
entity |
| Predicate | supportsConcessionType |
P37725
|
FINISHED |
| Object | youth fares |
—
|
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: youth fares | Statement: [Hop, supportsConcessionType, youth fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsConcessionType Context triple: [Hop, supportsConcessionType, youth fares]
-
A.
concessionType
chosen
Indicates the specific kind or category of concession (such as a discount, exemption, or special allowance) that applies in a given context.
-
B.
hasConcessions
Indicates that one entity provides or contains concession facilities, services, or rights (such as food, drink, or merchandise sales) for another entity or within a given context.
-
C.
hasConcessionaire
Indicates that one entity is designated as the concessionaire (holder of operating or usage rights under a concession) for another entity.
-
D.
concessionExtended
Indicates that one party has granted or prolonged a special allowance, discount, or favorable term to another party.
-
E.
concessionStart
Indicates the point in a discourse or text where a concession begins, marking a shift to acknowledging a contrasting or limiting consideration relative to what was previously stated.
- 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_69ad85ad38e48190b7660c5118a35289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb92c20fc81909b5debced20ec083 |
completed | March 8, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69adadfcbc38819080852c18240451c5 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:15 p.m.