Triple
T5055217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Julius No |
E113883
|
entity |
| Predicate | introducedInFranchise |
P8259
|
FINISHED |
| Object | first James Bond film |
—
|
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: first James Bond film | Statement: [Dr. Julius No, introducedInFranchise, first James Bond film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedInFranchise Context triple: [Dr. Julius No, introducedInFranchise, first James Bond film]
-
A.
introducedFor
Indicates that one entity was presented or brought to the attention of another entity for a specific purpose or role.
-
B.
introducedInYear
Indicates the year in which something was first introduced, launched, or made available.
-
C.
introducedDuring
chosen
Indicates that one entity was first brought into existence, use, or awareness within the time period, event, or context specified by the other entity.
-
D.
introducedVia
Indicates that one entity was brought to the attention, presence, or awareness of another entity through a specific intermediary, method, or channel.
-
E.
introducedOnTV
Indicates that an entity was first presented, revealed, or made known to the public through a television broadcast.
- 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_69bd443aa1f88190abb992d138f2cf42 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd744ccb888190a8a0ddd7c4d62f35 |
completed | March 20, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69bd715479f08190933604aebd34414f |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.