Triple
T36954317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Athena’s Fortune |
E914149
|
entity |
| Predicate | emissaryLedgerRewards |
P187627
|
FINISHED |
| Object | Cosmetic items |
—
|
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: Cosmetic items | Statement: [Athena’s Fortune, emissaryLedgerRewards, Cosmetic items]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emissaryLedgerRewards Context triple: [Athena’s Fortune, emissaryLedgerRewards, Cosmetic items]
-
A.
emissaryLedgerRewardType
chosen
Indicates the type or category of reward granted through an emissary ledger or emissary-related reward system.
-
B.
emissaryLedger
Indicates a relationship where one party maintains or uses a record (ledger) tracking the activities, communications, or obligations of an emissary or representative.
-
C.
rewardRecipient
Indicates the entity that receives a reward as a result of some action, event, or decision.
-
D.
monetaryReward
Indicates that one entity provides or promises a payment of money to another as compensation, incentive, or prize.
-
E.
grantedAsRewardFor
Indicates that something is given to an entity specifically as a reward for a particular action, achievement, or service.
- 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_69f76e8b28848190abd81fe7a7374910 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:13 p.m.