Triple
T20708636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Round of 16 at 1998 FIFA World Cup |
E508972
|
entity |
| Predicate | cityHostedIn |
P19642
|
FINISHED |
| Object | Lens |
—
|
NE NERFINISHED |
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: Lens | Statement: [Round of 16 at 1998 FIFA World Cup, cityHostedIn, Lens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lens Context triple: [Round of 16 at 1998 FIFA World Cup, cityHostedIn, Lens]
-
A.
Lens
chosen
Lens is a commune in northern France known for its mining heritage and the Louvre-Lens art museum.
-
B.
Lens
The Lens is a powerful, telepathic, and semi-sentient device in the Lensman series that grants its wearer enhanced mental abilities and authority as a Galactic Patrol officer.
-
C.
Lens
Lens is a locality situated near the community of Montana, likely within the same regional area.
-
D.
Lenses
Lenses are Snapchat’s interactive augmented reality filters that overlay animations and effects onto users’ faces and surroundings in real time.
-
E.
Lenti
Lenti is a small town in southwestern Hungary known for its thermal spa and proximity to the Slovenian border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c40ad88190b81f77695366d328 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1952e888190877b79933970f7b0 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 12:14 p.m.