Triple
T34547115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polaroid photography |
E886955
|
entity |
| Predicate | firstConsumerIntroductionYear |
P205464
|
FINISHED |
| Object | 1948 |
—
|
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: 1948 | Statement: [Polaroid photography, firstConsumerIntroductionYear, 1948]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstConsumerIntroductionYear Context triple: [Polaroid photography, firstConsumerIntroductionYear, 1948]
-
A.
firstCreationYear
Indicates the year in which something was first created or originally produced.
-
B.
firstCompleterYear
Indicates the calendar or academic year in which an entity first completed a specified program, requirement, or activity.
-
C.
firstArrivalYear
Indicates the calendar year in which an entity first arrived at or was initially present in a specified place or context.
-
D.
firstRunningYear
Indicates the year in which something (such as an event, service, or operation) first began running or was initially active.
-
E.
firstReviewYear
Indicates the calendar year in which an entity received its first review.
- F. None of above. chosen
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_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 2:02 a.m.