Triple
T18344724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revolution Ventures |
E439505
|
entity |
| Predicate | investmentModel |
P4851
|
FINISHED |
| Object | lead or co-lead Series A and early growth rounds |
—
|
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: lead or co-lead Series A and early growth rounds | Statement: [Revolution Ventures, investmentModel, lead or co-lead Series A and early growth rounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: investmentModel Context triple: [Revolution Ventures, investmentModel, lead or co-lead Series A and early growth rounds]
-
A.
investmentOptions
Indicates that one entity offers, defines, or is associated with possible ways another entity can allocate resources or capital.
-
B.
investmentType
chosen
Indicates the specific category or nature of an investment associated with an entity or transaction.
-
C.
investmentTarget
Indicates that one entity is the object or recipient of another entity’s investment.
-
D.
vestmentStyle
Indicates the style or type of clothing or ceremonial garments associated with an entity.
-
E.
investment
Indicates a relationship where one party allocates resources (such as money, time, or effort) into something with the expectation of future benefit or return.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e514f2c8ec8190b045482846a68204 |
completed | April 19, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69e44fe91bc08190906518e1b120fcf0 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:37 a.m.