Triple
T30984189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LSE: HOF |
E789473
|
entity |
| Predicate | languageOfTradingVenue |
P59059
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [LSE: HOF, languageOfTradingVenue, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfTradingVenue Context triple: [LSE: HOF, languageOfTradingVenue, English]
-
A.
languageOfPrimaryMarkets
Indicates the primary language or languages used in the main markets where an entity operates or targets its products or services.
-
B.
languageUsedInTrade
Indicates that a particular language is employed as a medium of communication in trade or commercial transactions between parties.
-
C.
identifiesTradingVenue
Indicates that one entity specifies or designates the trading venue associated with another entity or transaction.
-
D.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
E.
languageOfVenue
chosen
Indicates the language primarily used or officially designated for communication at a given venue.
- 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_69f224c550b081909ddfceb0c3d03bdd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
Created at: April 29, 2026, 8:55 p.m.