Triple
T16741711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Multicam family |
E406848
|
entity |
| Predicate | includesPattern |
P8151
|
FINISHED |
| Object | MultiCam Transitional |
E757261
|
NE 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: MultiCam Transitional | Statement: [Multicam family, includesPattern, MultiCam Transitional]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MultiCam Transitional Context triple: [Multicam family, includesPattern, MultiCam Transitional]
-
A.
MultiCam
chosen
MultiCam is a widely used camouflage pattern designed to provide effective concealment across a broad range of environments and lighting conditions, especially for military and tactical applications.
-
B.
Caméra One
Caméra One is a French film production company known for producing acclaimed art-house and auteur-driven movies.
-
C.
Cámara Base
Cámara Base is an Argentine research station in Antarctica that operates primarily during the austral summer to support scientific and logistical activities in the region.
-
D.
Megacam
Megacam is a wide-field optical imaging camera used on large ground-based telescopes for deep, high-resolution astronomical surveys.
-
E.
Cámara
Cámara is an Argentine Navy officer known for his service in Argentina's naval forces.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c3f49808190b543d8da34031f3d |
completed | April 18, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d52d88081909695a08d00bd2257 |
completed | May 10, 2026, 2:59 p.m. |
Created at: April 10, 2026, 5:21 a.m.