Triple
T37462334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open the Waygate |
E930947
|
entity |
| Predicate | rewardCardEffect |
P190725
|
FINISHED |
| Object | Take an extra turn. |
—
|
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: Take an extra turn. | Statement: [Open the Waygate, rewardCardEffect, Take an extra turn.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rewardCardEffect Context triple: [Open the Waygate, rewardCardEffect, Take an extra turn.]
-
A.
rewardCard
Indicates that one entity provides or is associated with a reward card (such as a loyalty or points card) for another entity.
-
B.
rewardCardName
Indicates the name or title assigned to a specific reward card associated with an entity.
-
C.
rewardUse
Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
-
D.
rewardBrand
Indicates that one entity grants or associates a reward with a particular brand.
-
E.
rewardRedemption
Indicates the act of exchanging accumulated rewards, points, or benefits for goods, services, or other forms of value.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcce2cf9188190b3f65b362203a6a3 |
completed | May 7, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fccdd2d84481909a7ce22407def9c7 |
completed | May 7, 2026, 5:37 p.m. |
Created at: May 3, 2026, 4:17 p.m.