Triple
T12176901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2317.TW |
E290110
|
entity |
| Predicate | tradingLotUnit |
P103200
|
FINISHED |
| Object | shares |
—
|
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: shares | Statement: [2317.TW, tradingLotUnit, shares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tradingLotUnit Context triple: [2317.TW, tradingLotUnit, shares]
-
A.
hasLotSize
Indicates that an entity possesses a specific amount or extent of physical area, typically referring to the size of a parcel of land or property lot.
-
B.
hasLotSizeType
Indicates the classification or category used to describe the size of a lot or parcel.
-
C.
minorUnitsPerUnit
Indicates the number of smaller sub-units that collectively make up one whole unit in a given measurement or currency system.
-
D.
fractionalUnitCode
Indicates the code that specifies the fractional unit or sub-division of a primary unit used in a measurement or quantity.
-
E.
minimumPriceFluctuation
Indicates the smallest allowable change or increment by which a price is permitted to move in the given context.
- F. None of above. chosen
Provenance (4 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91621ca6c81908365732f361aef13 |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150e85348190b9b47cda4a17dcd0 |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d916165c708190bf0745e125589f46 |
completed | April 10, 2026, 3:24 p.m. |
Created at: April 8, 2026, 9:50 p.m.