Triple
T4614187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Match Group |
E100826
|
entity |
| Predicate | notableBrand |
P1500
|
FINISHED |
| Object | Tinder |
E100825
|
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: Tinder | Statement: [Match Group, notableBrand, Tinder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tinder Context triple: [Match Group, notableBrand, Tinder]
-
A.
Grindr
Grindr is a location-based social networking and online dating app primarily used by gay, bi, trans, and queer people to meet and connect.
-
B.
Match.com
Match.com is one of the earliest and most prominent online dating services, connecting singles worldwide through its web and mobile platforms.
-
C.
Meetic
Meetic is a popular European online dating service that connects singles through web and mobile platforms.
-
D.
Tinder (historically, via Match Group prior to spin-off)
chosen
Tinder (historically, via Match Group prior to its spin-off) is a leading location-based dating and social discovery app best known for popularizing the swipe-based matching interface.
-
E.
Burbn
Burbn was a location-based photo-sharing startup that served as the precursor to and foundation for what became Instagram.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59c2678c8190ab8f9420e866521d |
completed | March 20, 2026, 2:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be1029dc8c81908ec7d0ddd23428b4 |
completed | March 21, 2026, 3:27 a.m. |
Created at: March 20, 2026, 1:12 p.m.