Triple
T12880013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megara municipality |
E308066
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Kinetta
Kinetta is a coastal settlement in Greece known for its beaches and holiday homes, located within the municipality of Megara in the Attica region.
|
E1007832
|
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: Kinetta | Statement: [Megara municipality, containsSettlement, Kinetta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kinetta Context triple: [Megara municipality, containsSettlement, Kinetta]
-
A.
Nengone
Nengone is an Austronesian language spoken primarily by the indigenous Kanak people on Maré Island in New Caledonia.
-
B.
Ménaka
Ménaka is a town in eastern Mali that serves as an important administrative and trading center in the Sahel region.
-
C.
Meya
Meya is a variant form of the given name Maya, often used as a feminine personal name.
-
D.
Kenga
Kenga is a Central Sudanic language spoken primarily by the Kenga people in Chad.
-
E.
Premikudu
Premikudu is the Telugu-dubbed version of the popular 1994 Tamil romantic action film "Kadhalan," starring Prabhu Deva and Nagma and directed by Shankar.
- 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: Kinetta Triple: [Megara municipality, containsSettlement, Kinetta]
Generated description
Kinetta is a coastal settlement in Greece known for its beaches and holiday homes, located within the municipality of Megara in the Attica region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kinetta Target entity description: Kinetta is a coastal settlement in Greece known for its beaches and holiday homes, located within the municipality of Megara in the Attica region.
-
A.
Nengone
Nengone is an Austronesian language spoken primarily by the indigenous Kanak people on Maré Island in New Caledonia.
-
B.
Ménaka
Ménaka is a town in eastern Mali that serves as an important administrative and trading center in the Sahel region.
-
C.
Meya
Meya is a variant form of the given name Maya, often used as a feminine personal name.
-
D.
Kenga
Kenga is a Central Sudanic language spoken primarily by the Kenga people in Chad.
-
E.
Premikudu
Premikudu is the Telugu-dubbed version of the popular 1994 Tamil romantic action film "Kadhalan," starring Prabhu Deva and Nagma and directed by Shankar.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970fc1e488190a0c48039f6213e62 |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bba33c081909c0050ff7b868a8e |
completed | May 3, 2026, 12:50 a.m. |
| NEDg | Description generation | batch_69f69df1032881909255e506ddfd9c9f |
completed | May 3, 2026, 12:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69ea645a0819095edc112b9ed9bff |
completed | May 3, 2026, 1:02 a.m. |
Created at: April 9, 2026, 5:39 p.m.