Triple
T13470540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | wedding of Peleus and Thetis |
E311617
|
entity |
| Predicate | goldenAppleInscription |
P4758
|
FINISHED |
| Object | to the fairest |
—
|
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: to the fairest | Statement: [wedding of Peleus and Thetis, goldenAppleInscription, to the fairest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goldenAppleInscription Context triple: [wedding of Peleus and Thetis, goldenAppleInscription, to the fairest]
-
A.
goldenBootShared
Indicates that the Golden Boot award for top scorer in a competition was shared between two or more players rather than awarded to a single individual.
-
B.
materialTypicallyInscribedOn
Indicates the material that is most commonly used as the surface or medium on which something is inscribed.
-
C.
standardGoldContent
Indicates the specified standard or required amount of gold contained in something, typically as a measure of purity or value.
-
D.
hasLanternInscription
Indicates that an entity bears or contains an inscription specifically on or associated with a lantern.
-
E.
isInscribedOn
chosen
Indicates that text, symbols, or markings are written, carved, or otherwise permanently placed onto the surface of an object.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf22e5f88190b1078f006c8ef7c0 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.