Triple
T30300803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple September 2015 event |
E770646
|
entity |
| Predicate | includedSegment |
P144384
|
FINISHED |
| Object | Apple Watch updates |
—
|
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: Apple Watch updates | Statement: [Apple September 2015 event, includedSegment, Apple Watch updates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedSegment Context triple: [Apple September 2015 event, includedSegment, Apple Watch updates]
-
A.
appearsInSegmentOf
chosen
Indicates that one entity occurs within, or is featured as part of, a specific segment or subsection of another entity.
-
B.
includesCapSegments
Indicates that an entity contains or is composed of one or more capitalized text segments as part of its structure or content.
-
C.
intendedSegment
Indicates that one entity is the target or designated recipient segment for another entity (such as a message, offer, or action).
-
D.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
E.
hasSegmentWith
Indicates that an entity contains or includes at least one segment that satisfies a specified condition or matches a given segment.
- 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_69f224881b948190b8c4921b250a44a3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a006ef900148190ba52daf566882a03 |
completed | May 10, 2026, 11:41 a.m. |
| PD | Predicate disambiguation | batch_6a006c76ae748190bfe466d7d17d321e |
completed | May 10, 2026, 11:31 a.m. |
Created at: April 29, 2026, 7:48 p.m.