Triple
T34547116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polaroid photography |
E886955
|
entity |
| Predicate | firstCameraModel |
P5101
|
FINISHED |
| Object | Polaroid Land Camera Model 95 |
E886956
|
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: Polaroid Land Camera Model 95 | Statement: [Polaroid photography, firstCameraModel, Polaroid Land Camera Model 95]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstCameraModel Context triple: [Polaroid photography, firstCameraModel, Polaroid Land Camera Model 95]
-
A.
firstCameraBody
Indicates that one camera body is the initial or primary camera body associated with a given photographer, setup, or camera system.
-
B.
firstConsumerCameraRelease
Indicates the event or date when a camera model was first released to the consumer market.
-
C.
firstModel
chosen
Indicates that an entity is the initial or earliest model/version in a sequence or series of models.
-
D.
mainCameraSensor
Indicates that an entity functions as the primary camera sensor for another entity.
-
E.
tipoDeCámara
Indicates the specific type or category of camera associated with an entity.
- F. None of above.
Provenance (4 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_69f349cff89081908f91e0b064f4833e |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3729f5443c8190a1e372c3ad6eafbd |
completed | June 21, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2:02 a.m.