Triple
T26682055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bakelite |
E672638
|
entity |
| Predicate | countryOfFirstCommercialization |
P92926
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Bakelite, countryOfFirstCommercialization, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfFirstCommercialization Context triple: [Bakelite, countryOfFirstCommercialization, United States]
-
A.
firstCommercialNetworkCountry
Indicates the country where a given entity first launched or operated its commercial network.
-
B.
countryOfFirstMarketing
chosen
Indicates the country where a product was first introduced or made available on the market.
-
C.
wasFirstCommercializedBy
Indicates that the subject was initially brought to market or made commercially available by the object.
-
D.
countryOfFirstRelease
Indicates the country in which a work (such as a film, game, or product) was first officially released.
-
E.
locationOfFirstCommercialUse
Indicates the place where something was first used commercially.
- 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_69eecda13424819092b17942c4edf722 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: April 27, 2026, 3:20 a.m.