Triple
T24716123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enterprise Securities Market |
E612165
|
entity |
| Predicate | hasListingBenefits |
P2188
|
FINISHED |
| Object | potentially lower regulatory burden than main market |
—
|
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: potentially lower regulatory burden than main market | Statement: [Enterprise Securities Market, hasListingBenefits, potentially lower regulatory burden than main market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasListingBenefits Context triple: [Enterprise Securities Market, hasListingBenefits, potentially lower regulatory burden than main market]
-
A.
hasBenefit
chosen
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
hasBenefitType
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
C.
benefitAvailableAt
Indicates that a particular benefit can be obtained, accessed, or used at a specified location, time, or context.
-
D.
benefitAppliesTo
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
E.
hasBenefitDesign
Indicates that an entity possesses or is associated with a particular benefit-related design or configuration.
- 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_69e2d7d6e7a48190bb43b0d8bb1137a0 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 3:36 a.m.