Triple
T17941134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Et Meydanı |
E448589
|
entity |
| Predicate | nameMeaning |
P453
|
FINISHED |
| Object |
Meat Square
Meat Square is a public square in Istanbul, Turkey, historically associated with the city’s meat markets and trade.
|
E1297998
|
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: Meat Square | Statement: [Et Meydanı, nameMeaning, Meat Square]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meat Square Context triple: [Et Meydanı, nameMeaning, Meat Square]
-
A.
Kousba
Kousba is a town in northern Lebanon located in the Koura District, known for its olive groves and traditional Lebanese rural character.
-
B.
Mehunaise
Mehunaise is the French demonym for a female inhabitant of the town of Mehun-sur-Yèvre in central France.
-
C.
Sarma
Sarma is a traditional dish of vine or cabbage leaves wrapped around a savory filling, commonly enjoyed throughout Turkish and other Balkan and Middle Eastern cuisines.
-
D.
Meehni
Meehni is one of the three iconic sandstone rock pillars known as the Three Sisters in the Blue Mountains of New South Wales, Australia.
-
E.
Salo
Salo is a town in southwestern Finland known for its electronics industry history and location along the Salo River.
- 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: Meat Square Triple: [Et Meydanı, nameMeaning, Meat Square]
Generated description
Meat Square is a public square in Istanbul, Turkey, historically associated with the city’s meat markets and trade.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meat Square Target entity description: Meat Square is a public square in Istanbul, Turkey, historically associated with the city’s meat markets and trade.
-
A.
Kousba
Kousba is a town in northern Lebanon located in the Koura District, known for its olive groves and traditional Lebanese rural character.
-
B.
Mehunaise
Mehunaise is the French demonym for a female inhabitant of the town of Mehun-sur-Yèvre in central France.
-
C.
Sarma
Sarma is a traditional dish of vine or cabbage leaves wrapped around a savory filling, commonly enjoyed throughout Turkish and other Balkan and Middle Eastern cuisines.
-
D.
Meehni
Meehni is one of the three iconic sandstone rock pillars known as the Three Sisters in the Blue Mountains of New South Wales, Australia.
-
E.
Salo
Salo is a town in southwestern Finland known for its electronics industry history and location along the Salo River.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad95f4608190b1ebb45944218f07 |
completed | April 19, 2026, 10:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a032914b7008190a7207d93f865ea8f |
completed | May 12, 2026, 1:20 p.m. |
| NEDg | Description generation | batch_6a032b598bd881909f53df8f82799b6b |
completed | May 12, 2026, 1:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a032c42d0a08190b2665adafaffdca7 |
completed | May 12, 2026, 1:33 p.m. |
Created at: April 10, 2026, 10:21 a.m.