Triple
T25006365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wall |
E625849
|
entity |
| Predicate | hasMarketBeyond |
P169204
|
FINISHED |
| Object | Faerie market |
—
|
NE NERFINISHED |
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: Faerie market | Statement: [Wall, hasMarketBeyond, Faerie market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketBeyond Context triple: [Wall, hasMarketBeyond, Faerie market]
-
A.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
B.
hasMarketFocus
Indicates that an entity concentrates its business activities, products, or services on a particular market or customer segment.
-
C.
hasMarketStructure
Indicates that one entity possesses, follows, or is characterized by a particular market structure in an economic or commercial context.
-
D.
hasMarketData
Indicates that an entity possesses or is associated with relevant market-related information or statistics.
-
E.
hasIntermediateMarket
Indicates that there exists a secondary or intermediary market through which the subject’s goods, services, or assets are traded or distributed before reaching the final market.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f67d691a948190afa7fb19ae7d4ac5 |
completed | May 2, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67c9ec1708190b26ccf402ed7b106 |
completed | May 2, 2026, 10:37 p.m. |
Created at: April 18, 2026, 6:05 a.m.