Triple
T15160717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panerai |
E362205
|
entity |
| Predicate | historicalProduct |
P14355
|
FINISHED |
| Object | military-issue dive watches |
—
|
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: military-issue dive watches | Statement: [Panerai, historicalProduct, military-issue dive watches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalProduct Context triple: [Panerai, historicalProduct, military-issue dive watches]
-
A.
keyHistoricalProduct
chosen
Indicates that the product played a significant or defining role in the historical development, identity, or evolution of the associated entity.
-
B.
hasProductionHistory
Indicates that an entity is associated with a record or account of its past production activities, processes, or outputs.
-
C.
historicalType
Indicates that one entity classifies or characterizes another in terms of its role, status, or category within a historical context.
-
D.
historicalVersion
Indicates that one entity represents an earlier or past version in the history or evolution of another entity.
-
E.
historicallyStoredGoods
Indicates that an entity has previously stored certain goods at some time in the past.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060f2efc8190aa0eb5fb8d4ce085 |
completed | April 15, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9779acc81908ed2dad382c42dca |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:08 a.m.