Triple
T8401148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mass Transportation Demonstration Program |
E198172
|
entity |
| Predicate | knowledgeOutput |
P81810
|
FINISHED |
| Object | best practices for transit operations |
—
|
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: best practices for transit operations | Statement: [Mass Transportation Demonstration Program, knowledgeOutput, best practices for transit operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knowledgeOutput Context triple: [Mass Transportation Demonstration Program, knowledgeOutput, best practices for transit operations]
-
A.
knowledgeType
Indicates the specific category or nature of knowledge associated with an entity or statement (e.g., factual, procedural, conceptual).
-
B.
knows
Indicates that one entity has knowledge or awareness of another entity or piece of information.
-
C.
knowledgeExchange
Indicates a reciprocal sharing or transfer of knowledge, information, or expertise between entities.
-
D.
usesKnowledgeOf
Indicates that one entity applies or draws upon the knowledge possessed by another entity in performing an action or achieving a result.
-
E.
viewOnKnowledge
Indicates the perspective, stance, or opinion one entity holds regarding another entity’s knowledge or understanding.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb824da3148190bfa3a1abfdfa02de |
completed | March 31, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76da264881909483b835e1db06da |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 6:04 p.m.