Triple
T27732903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | System.TimeSpan |
E697470
|
entity |
| Predicate | hasUnderlyingUnit |
P28578
|
FINISHED |
| Object | tick |
—
|
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: tick | Statement: [System.TimeSpan, hasUnderlyingUnit, tick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnderlyingUnit Context triple: [System.TimeSpan, hasUnderlyingUnit, tick]
-
A.
hasUnderlyingEntity
Indicates that one entity serves as the fundamental or base entity upon which another entity is conceptually or structurally built.
-
B.
hasUnitOf
chosen
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
C.
hasUnderlyingMarket
Indicates that one entity is based on, derives its value from, or is traded with reference to another entity that serves as its fundamental market.
-
D.
hasUnderlyingIssuer
Indicates that one entity serves as the fundamental or primary issuer behind another entity, such as a financial instrument or structured product.
-
E.
hasUnderlyingSector
Indicates that one entity is fundamentally based in, categorized within, or primarily associated with a particular economic or industry sector.
- 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_69ef590c3e288190ad54d2465af8ca4e |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 27, 2026, 3:12 p.m.