Triple
T14421108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amir Shinar |
E357584
|
entity |
| Predicate | coFounded |
P104
|
FINISHED |
| Object | Waze |
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 | Statement: [Amir Shinar, coFounded, Waze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waze Context triple: [Amir Shinar, coFounded, Waze]
-
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.
MapQuest
MapQuest is an early online mapping and driving directions service that became one of the first widely used web-based navigation tools.
-
D.
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.
-
E.
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.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91102c3c81908f571a1fff3bdd47 |
completed | April 14, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a38003c819083f276fcaae52da9 |
completed | May 8, 2026, 5:52 a.m. |
Created at: April 10, 2026, 1:18 a.m.