Triple
T23222120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura Deming |
E580921
|
entity |
| Predicate | areaOfInvestment |
P45042
|
FINISHED |
| Object | biotechnology startups |
—
|
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: biotechnology startups | Statement: [Laura Deming, areaOfInvestment, biotechnology startups]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaOfInvestment Context triple: [Laura Deming, areaOfInvestment, biotechnology startups]
-
A.
investmentScope
chosen
Indicates the range or boundaries of activities, assets, or sectors that an investment is intended or allowed to cover.
-
B.
investsIn
Indicates that one entity allocates resources, typically money or capital, into another entity with the expectation of future returns or benefits.
-
C.
investmentType
Indicates the specific category or nature of an investment associated with an entity or transaction.
-
D.
investmentTarget
Indicates that one entity is the object or recipient of another entity’s investment.
-
E.
vestments
Indicates that one entity is wearing or is ceremonially clothed in special religious or official garments associated with a role or office.
- 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_69e246043c48819089bae72c9a9c306c |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f1922a452c81909b48df157643f6bd |
completed | April 29, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69effcccee508190a7ae311fdd319806 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:08 p.m.