Triple
T78901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject |
E1582
|
entity | |
| Predicate | commercial |
P3849
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Facebook, commercial, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commercial Context triple: [Facebook, commercial, true]
-
A.
commercialized
Indicates that something has been developed, marketed, or exploited for profit in a commercial context.
-
B.
market
Indicates the act of promoting, advertising, or selling a product, service, or idea to potential buyers or target audiences.
-
C.
commercializedIn
Indicates that something has been brought to market or made available for commercial sale or use within a specified place or context.
-
D.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
E.
export
Indicates that one entity sends goods, services, or data out from its own domain or territory to another entity or external destination.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eb126b48190b410b859c1be99aa |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a24fcf5a88819088c5fa4c08476358 |
completed | Feb. 28, 2026, 2:15 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.