Triple
T4614158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Match Group |
E100826
|
entity |
| Predicate | operatedPlatform |
P1292
|
FINISHED |
| Object |
Meetic
Meetic is a popular European online dating service that connects singles through web and mobile platforms.
|
E461303
|
NE FINISHED |
How this triple was built (4 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: Meetic | Statement: [Match Group, operatedPlatform, Meetic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meetic Context triple: [Match Group, operatedPlatform, Meetic]
-
A.
Match.com
Match.com is one of the earliest and most prominent online dating services, connecting singles worldwide through its web and mobile platforms.
-
B.
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.
-
C.
Matchmakers
Matchmakers is a popular Ukrainian comedy television series produced by Kvartal 95 Studio that follows the humorous clashes and relationships between two very different families.
-
D.
PlentyOfFish
PlentyOfFish is a popular online dating service and app known for its large user base and free-to-use features.
-
E.
OkCupid
OkCupid is an online dating platform known for its detailed questionnaires and algorithm-based matching that focuses on compatibility and inclusivity.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Meetic Triple: [Match Group, operatedPlatform, Meetic]
Generated description
Meetic is a popular European online dating service that connects singles through web and mobile platforms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meetic Target entity description: Meetic is a popular European online dating service that connects singles through web and mobile platforms.
-
A.
Match.com
Match.com is one of the earliest and most prominent online dating services, connecting singles worldwide through its web and mobile platforms.
-
B.
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.
-
C.
Matchmakers
Matchmakers is a popular Ukrainian comedy television series produced by Kvartal 95 Studio that follows the humorous clashes and relationships between two very different families.
-
D.
PlentyOfFish
PlentyOfFish is a popular online dating service and app known for its large user base and free-to-use features.
-
E.
OkCupid
OkCupid is an online dating platform known for its detailed questionnaires and algorithm-based matching that focuses on compatibility and inclusivity.
- F. None of above. chosen
Provenance (5 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_69bd6234e8108190b985270b9ddd1f3a |
completed | March 20, 2026, 3:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be035629248190a8723b5f1f9e57bc |
completed | March 21, 2026, 2:32 a.m. |
| NEDg | Description generation | batch_69be04ad843c8190b3c8dfa4a46e727b |
completed | March 21, 2026, 2:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be0529868c8190b20e8966315b263a |
completed | March 21, 2026, 2:40 a.m. |
Created at: March 20, 2026, 1:12 p.m.