Triple
T9002086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DVD |
E215060
|
entity |
| Predicate | commercialIntroductionYear |
P50676
|
FINISHED |
| Object | 1996 |
—
|
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: 1996 | Statement: [DVD, commercialIntroductionYear, 1996]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commercialIntroductionYear Context triple: [DVD, commercialIntroductionYear, 1996]
-
A.
incorporationYear
Indicates the calendar year in which an organization or entity was formally incorporated or legally established.
-
B.
yearFirstDelivered
chosen
Indicates the calendar year in which something (such as a product, service, or item) was first delivered or made available.
-
C.
commercialIntroduction
Indicates that one entity introduces or connects another entity to a commercial opportunity, partner, product, or service for business purposes.
-
D.
demonstrationYear
Indicates the year in which a demonstration, display, or public showing of something took place.
-
E.
coupeIntroductionYear
Indicates the year in which a coupe model was first introduced.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6956a6e08190bd3853a7c1c130eb |
completed | April 1, 2026, 12:39 a.m. |
| PD | Predicate disambiguation | batch_69cc5edd6cb48190b4fc6d6ca0418056 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:05 p.m.