Triple
T4351801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opti |
E98042
|
entity |
| Predicate | themeRepresentation |
P55707
|
FINISHED |
| Object | innovation |
—
|
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: innovation | Statement: [Opti, themeRepresentation, innovation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeRepresentation Context triple: [Opti, themeRepresentation, innovation]
-
A.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
B.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
C.
themeExamples
Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
-
D.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
-
E.
themedAs
Indicates that something is characterized, styled, or organized according to a particular theme or motif.
- 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351ab03488190a8900de98fb4a00e |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f51ed7c8190b7bf5f44b56b730d |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:15 p.m.