Triple
T7346433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MyTeksi |
E169391
|
entity |
| Predicate | rebrandedAs |
P65
|
FINISHED |
| Object | Grab |
E30981
|
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: Grab | Statement: [MyTeksi, rebrandedAs, Grab]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grab Context triple: [MyTeksi, rebrandedAs, Grab]
-
A.
Grab
chosen
Grab is a Southeast Asian super-app company best known for its ride-hailing, food delivery, and digital payments services.
-
B.
Grabs
Grabs is a municipality in the canton of St. Gallen in northeastern Switzerland, known for its Alpine setting near the Liechtenstein border.
-
C.
Grip
Grip is a small historic fishing village and archipelago off the coast of Kristiansund in western Norway, known for its picturesque wooden houses and old stave church.
-
D.
Get a Grip
Get a Grip is a 1993 hard rock album by Aerosmith that features hits like "Cryin'," "Crazy," and "Amazing" and marked a major commercial resurgence for the band.
-
E.
Get Em
"Get Em" is a track from Lil Wayne’s mixtape *Dedication 2*, showcasing his rapid-fire wordplay and punchline-heavy Southern rap style.
- 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0f0329c8190a0182e3bf62604e5 |
completed | March 27, 2026, 9:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83433ca8081909ab00d1fe3ab1041 |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:05 p.m.