Triple
T247779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F |
E5075
|
entity |
| Predicate | isHighlyTraded |
P6188
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [F, isHighlyTraded, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isHighlyTraded Context triple: [F, isHighlyTraded, true]
-
A.
isWidelyTraded
chosen
Indicates that an asset or item is frequently bought and sold across many participants or markets, resulting in high trading activity and liquidity.
-
B.
isMostTradedCurrency
Indicates that a currency is the one with the highest trading volume or frequency in a given market or context.
-
C.
tradedOn
Indicates that an asset, security, or instrument is bought and sold on a particular exchange or trading venue.
-
D.
trades
Indicates an exchange relationship where one party gives something of value to another in return for something else of value.
-
E.
isHeavilyWeightedToward
Indicates that something is strongly biased or disproportionately oriented in favor of one side, option, or aspect over others.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d154ebc819087a5c9dc4f62ff44 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b64ea3081908de626a0e1445bdb |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.