Triple
T20285044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Free Fall |
E509853
|
entity |
| Predicate | hasIntendedMarket |
P55993
|
FINISHED |
| Object | literary fiction market |
—
|
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: literary fiction market | Statement: [Free Fall, hasIntendedMarket, literary fiction market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntendedMarket Context triple: [Free Fall, hasIntendedMarket, literary fiction market]
-
A.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
B.
hasMarketingTarget
chosen
Indicates that an entity is aimed at or intended to appeal to a specific marketing audience or segment.
-
C.
hasTargetMarketPositioning
Indicates the specific market segment and competitive position that an offering is intended to occupy relative to alternatives.
-
D.
hasMarketFocus
Indicates that an entity concentrates its business activities, products, or services on a particular market or customer segment.
-
E.
hasMarketSegmentFor
Indicates that an entity targets or serves a specific market segment for its products or services.
- 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e67691516c81909f32b176edb6214c |
completed | April 20, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:05 a.m.