Triple
T10311176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melos |
E241892
|
entity |
| Predicate | knownInAntiquityFor |
P46173
|
FINISHED |
| Object | obsidian trade |
—
|
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: obsidian trade | Statement: [Melos, knownInAntiquityFor, obsidian trade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownInAntiquityFor Context triple: [Melos, knownInAntiquityFor, obsidian trade]
-
A.
discoveredInAntiquity
Indicates that something was found, identified, or recognized during ancient historical times rather than in the modern era.
-
B.
knownToAncientGreeks
Indicates that something was recognized, identified, or understood by people in ancient Greek societies.
-
C.
ancientNameOf
Indicates that one entity is the historical or ancient name by which the other entity was formerly known.
-
D.
reputationInAntiquity
chosen
Indicates the reputation or standing an entity had during ancient times.
-
E.
ancientCity
Indicates that the subject is a historically old or long-established city, typically originating from ancient times.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:47 a.m.