Triple
T16367282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thargelion |
E397468
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object |
Mounichion
Mounichion was an ancient Athenian month in the Attic calendar, roughly corresponding to parts of April and May, associated with various religious festivals and seasonal observances.
|
E1209172
|
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: Mounichion | Statement: [Thargelion, follows, Mounichion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mounichion Context triple: [Thargelion, follows, Mounichion]
-
A.
Maroneitai
Maroneitai were the ancient Greek inhabitants or ethnic group associated with the city of Maroneia in Thrace.
-
B.
Mourouj
Mourouj is a suburban town in northern Tunisia that forms part of the greater Tunis metropolitan area.
-
C.
Molyvos
Molyvos is a picturesque coastal town on the Greek island of Lesbos, known for its medieval castle, traditional stone houses, and scenic harbor.
-
D.
Maroneia
Maroneia is an ancient Greek city in Thrace, near the northern Aegean coast, known historically for its wine production and strategic harbor.
-
E.
Mourou
Mourou is the surname of Gérard Mourou, a French physicist and Nobel laureate known for pioneering chirped pulse amplification in laser physics.
- 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: Mounichion Triple: [Thargelion, follows, Mounichion]
Generated description
Mounichion was an ancient Athenian month in the Attic calendar, roughly corresponding to parts of April and May, associated with various religious festivals and seasonal observances.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mounichion Target entity description: Mounichion was an ancient Athenian month in the Attic calendar, roughly corresponding to parts of April and May, associated with various religious festivals and seasonal observances.
-
A.
Maroneitai
Maroneitai were the ancient Greek inhabitants or ethnic group associated with the city of Maroneia in Thrace.
-
B.
Mourouj
Mourouj is a suburban town in northern Tunisia that forms part of the greater Tunis metropolitan area.
-
C.
Molyvos
Molyvos is a picturesque coastal town on the Greek island of Lesbos, known for its medieval castle, traditional stone houses, and scenic harbor.
-
D.
Maroneia
Maroneia is an ancient Greek city in Thrace, near the northern Aegean coast, known historically for its wine production and strategic harbor.
-
E.
Mourou
Mourou is the surname of Gérard Mourou, a French physicist and Nobel laureate known for pioneering chirped pulse amplification in laser physics.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff3de3d88190a42cd708746c8bd0 |
completed | April 18, 2026, 3:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dc29f088190ba5d69ff3c12a251 |
completed | May 10, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_6a002ec2fd948190878af958d0b90ce6 |
completed | May 10, 2026, 7:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00312a4fc48190b6bd6ad9db71bb4d |
completed | May 10, 2026, 7:18 a.m. |
Created at: April 10, 2026, 5:08 a.m.