Triple

T13386014
Position Surface form Disambiguated ID Type / Status
Subject Spartan polis E319446 entity
Predicate socialInstitution P6110 FINISHED
Object syssitia
Syssitia were communal messes in ancient Sparta where male citizens regularly dined together, reinforcing social cohesion, military discipline, and equality among warriors.
 E1037134 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: syssitia | Statement: [Spartan polis, socialInstitution, syssitia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: syssitia
Context triple: [Spartan polis, socialInstitution, syssitia]
  • A. ssy
    ssy is the ISO 639-3 language code for Saho, a Cushitic language spoken primarily in Eritrea and Ethiopia.
  • B. SYP
    SYP is the ISO 4217 currency code for the Syrian pound, the official monetary unit of Syria.
  • C. SYR
    SYR is the three-letter ISO 3166-1 alpha-3 country code representing the Middle Eastern nation of Syria.
  • D. Sy
    Sy is the first name of Sy Gomberg, an American screenwriter and producer known for his work in mid-20th-century film and television.
  • E. Sy
    Sy is a Diameter-based interface in telecommunications networks used for policy and charging control between the PCRF and online charging systems.
  • 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: syssitia
Triple: [Spartan polis, socialInstitution, syssitia]
Generated description
Syssitia were communal messes in ancient Sparta where male citizens regularly dined together, reinforcing social cohesion, military discipline, and equality among warriors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: syssitia
Target entity description: Syssitia were communal messes in ancient Sparta where male citizens regularly dined together, reinforcing social cohesion, military discipline, and equality among warriors.
  • A. ssy
    ssy is the ISO 639-3 language code for Saho, a Cushitic language spoken primarily in Eritrea and Ethiopia.
  • B. SYP
    SYP is the ISO 4217 currency code for the Syrian pound, the official monetary unit of Syria.
  • C. SYR
    SYR is the three-letter ISO 3166-1 alpha-3 country code representing the Middle Eastern nation of Syria.
  • D. Sy
    Sy is a Diameter-based interface in telecommunications networks used for policy and charging control between the PCRF and online charging systems.
  • E. Sy
    Sy is the first name of Sy Gomberg, an American screenwriter and producer known for his work in mid-20th-century film and television.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadce96d1881909957fdd068a7f55d completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7268f9a908190843481dd313f5a11 completed May 3, 2026, 10:42 a.m.
NEDg Description generation batch_69f7272115f4819092e4fa0fd7f130b5 completed May 3, 2026, 10:44 a.m.
NED2 Entity disambiguation (via description) batch_69f72992483c8190873ba7050ad9e6fa completed May 3, 2026, 10:55 a.m.
Created at: April 9, 2026, 9:33 p.m.