Triple
T26966736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RP |
E679190
|
entity |
| Predicate | relationshipToLasVegas |
P199142
|
FINISHED |
| Object | Las Vegas algorithms correspond to ZPP, not RP |
—
|
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: Las Vegas algorithms correspond to ZPP, not RP | Statement: [RP, relationshipToLasVegas, Las Vegas algorithms correspond to ZPP, not RP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToLasVegas Context triple: [RP, relationshipToLasVegas, Las Vegas algorithms correspond to ZPP, not RP]
-
A.
relationshipToParis
Indicates the specific type of connection or association an entity has with Paris.
-
B.
relationshipToEva
Indicates a specified type of personal or social relationship that an entity has with Eva.
-
C.
relationshipToOrlando
Indicates the specific familial, social, or other personal connection that one entity has to the person or place named Orlando.
-
D.
relationshipToNPC
Indicates the type of interpersonal or narrative connection that one entity has with a non-player character (NPC).
-
E.
relationshipToLloyd
Indicates the specific type of personal or social relationship an entity has with Lloyd.
- 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69ff234f32888190a1d800a3bda432eb |
completed | May 9, 2026, 12:06 p.m. |
| PD | Predicate disambiguation | batch_69ff228ae9a0819083f4b97c10b923f4 |
completed | May 9, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69ff234e63648190a7b09a161029c8e2 |
completed | May 9, 2026, 12:06 p.m. |
Created at: April 27, 2026, 6:36 a.m.