Triple
T15585291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uri Levine |
E374604
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Waze navigation app |
E72080
|
NE 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: Waze navigation app | Statement: [Uri Levine, knownFor, Waze navigation app]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waze navigation app Context triple: [Uri Levine, knownFor, Waze navigation app]
-
A.
Waze
chosen
Waze is a community-driven GPS navigation app that provides real-time traffic updates, route guidance, and incident reports from its users.
-
B.
Maps.me
Maps.me is a mobile navigation app that provides offline maps and routing based on OpenStreetMap data.
-
C.
Nokia HERE Maps
Nokia HERE Maps is a mapping and navigation service offering offline maps, turn-by-turn directions, and location-based features across multiple devices and platforms.
-
D.
Baidu Maps
Baidu Maps is a Chinese web mapping and navigation service offering detailed maps, real-time traffic, and location-based services primarily for users in China.
-
E.
Map Man
Map Man is a BBC television series in which geographer and presenter Nicholas Crane retraces historic British journeys using original maps to explore their creation and impact.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e4900408190aadb48b001db4169 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4f71e48190a15eb0a2138f083f |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:11 a.m.