Triple

T3735448
Position Surface form Disambiguated ID Type / Status
Subject Musi River E79170 entity
Predicate alsoKnownAs P39 FINISHED
Object Musi
Musi is a river in Indonesia that flows through the city of Palembang in South Sumatra and serves as an important transportation and economic waterway.
 E383324 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: Musi | Statement: [Musi River, alsoKnownAs, Musi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Musi
Context triple: [Musi River, alsoKnownAs, Musi]
  • A. Mera
    Mera is a powerful Atlantean warrior and sorceress from DC Comics, best known as Aquaman’s ally and queen of Atlantis.
  • B. Bani
    Bani was a daughter of the prominent Indian freedom fighter and lawyer Chittaranjan (C. R.) Das.
  • C. Surmali
    Surmali was a historic town in the South Caucasus region, known as the administrative center of the Surmalu uezd in the Russian Empire and later part of present-day Turkey.
  • D. Mota
    Mota is an Oceanic language of northern Vanuatu, historically notable as a regional lingua franca and early mission language in the area.
  • E. Maino
    Maino is an Italian surname most notably associated with Sonia Gandhi, the former president of the Indian National Congress.
  • 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: Musi
Triple: [Musi River, alsoKnownAs, Musi]
Generated description
Musi is a river in Indonesia that flows through the city of Palembang in South Sumatra and serves as an important transportation and economic waterway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Musi
Target entity description: Musi is a river in Indonesia that flows through the city of Palembang in South Sumatra and serves as an important transportation and economic waterway.
  • A. Mera
    Mera is a powerful Atlantean warrior and sorceress from DC Comics, best known as Aquaman’s ally and queen of Atlantis.
  • B. Bani
    Bani was a daughter of the prominent Indian freedom fighter and lawyer Chittaranjan (C. R.) Das.
  • C. Surmali
    Surmali was a historic town in the South Caucasus region, known as the administrative center of the Surmalu uezd in the Russian Empire and later part of present-day Turkey.
  • D. Mota
    Mota is an Oceanic language of northern Vanuatu, historically notable as a regional lingua franca and early mission language in the area.
  • E. Maino
    Maino is an Italian surname most notably associated with Sonia Gandhi, the former president of the Indian National Congress.
  • 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_69ad8b0e4650819090ad7cef094285e8 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb3b399c819091b42209925c0d8f completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db1be1388190a887d9eca0f4f9b3 completed March 14, 2026, 3:50 a.m.
NEDg Description generation batch_69b4db81fd648190a9dd6f0ade21f14d completed March 14, 2026, 3:52 a.m.
NED2 Entity disambiguation (via description) batch_69b4dc1f3cc48190b1b53bc88a0c3577 completed March 14, 2026, 3:55 a.m.
Created at: March 8, 2026, 3:34 p.m.