Triple
T8679546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silas Lapham |
E205999
|
entity |
| Predicate | businessAsset |
P3488
|
FINISHED |
| Object | mineral paint formula |
—
|
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: mineral paint formula | Statement: [Silas Lapham, businessAsset, mineral paint formula]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessAsset Context triple: [Silas Lapham, businessAsset, mineral paint formula]
-
A.
businessBase
Indicates that one entity serves as the primary business foundation, core location, or main operational base for another entity.
-
B.
notableAsset
chosen
Indicates that an entity possesses or is associated with an asset that is particularly significant, prominent, or noteworthy in relation to it.
-
C.
assetType
Indicates the specific category or classification of an asset within a broader asset framework or system.
-
D.
economicProperty
Indicates that an entity possesses a specific economic characteristic, attribute, or condition, such as value, cost, or financial status, in relation to another entity or context.
-
E.
businessFunction
Indicates the specific role, activity, or operational function that an entity performs within a business context.
- 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_69ca835379688190aa06b9d98e684d58 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4ae6d19c8190be003f7901c0468d |
completed | March 31, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69cc4567b5c881908d9ec5dcfc783fac |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:32 p.m.