Triple

T11882719
Position Surface form Disambiguated ID Type / Status
Subject Ecclesiazusae E282696 entity
Predicate featuresCharacter P626 FINISHED
Object Chremes
Chremes is a stock comic character from ancient Greek drama, often portrayed as an older, somewhat foolish or gullible man.
 E951242 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: Chremes | Statement: [Ecclesiazusae, featuresCharacter, Chremes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Chremes
Context triple: [Ecclesiazusae, featuresCharacter, Chremes]
  • A. Onchesmos
    Onchesmos was an ancient Greek port city in Epirus, located where the modern Albanian coastal city of Saranda now stands.
  • B. Hermenches
    Hermenches is a small rural municipality in the canton of Vaud in western Switzerland.
  • C. Damaskinos
    Damaskinos is a Greek-origin surname historically associated with notable religious and cultural figures.
  • D. Stagoi
    Stagoi is a town in central Greece, historically associated with the nearby Meteora monasteries and serving as a local religious and administrative center.
  • E. Carthaginian cothon
    The Carthaginian cothon was a fortified, artificial harbor complex at Carthage that served as a key naval base and shipyard for the city’s powerful maritime fleet.
  • 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: Chremes
Triple: [Ecclesiazusae, featuresCharacter, Chremes]
Generated description
Chremes is a stock comic character from ancient Greek drama, often portrayed as an older, somewhat foolish or gullible man.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Chremes
Target entity description: Chremes is a stock comic character from ancient Greek drama, often portrayed as an older, somewhat foolish or gullible man.
  • A. Onchesmos
    Onchesmos was an ancient Greek port city in Epirus, located where the modern Albanian coastal city of Saranda now stands.
  • B. Hermenches
    Hermenches is a small rural municipality in the canton of Vaud in western Switzerland.
  • C. Damaskinos
    Damaskinos is a Greek-origin surname historically associated with notable religious and cultural figures.
  • D. Stagoi
    Stagoi is a town in central Greece, historically associated with the nearby Meteora monasteries and serving as a local religious and administrative center.
  • E. Carthaginian cothon
    The Carthaginian cothon was a fortified, artificial harbor complex at Carthage that served as a key naval base and shipyard for the city’s powerful maritime fleet.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d39d2934819093b9f7006f45e5cb completed April 10, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69f281e6f8888190bc8495b1261a86df completed April 29, 2026, 10:10 p.m.
NEDg Description generation batch_69f28c2590608190b6470f1b67f06e0f completed April 29, 2026, 10:54 p.m.
NED2 Entity disambiguation (via description) batch_69f28f4cb01c8190abf0397d14a3548c completed April 29, 2026, 11:07 p.m.
Created at: April 8, 2026, 9:44 p.m.