Triple

T5106960
Position Surface form Disambiguated ID Type / Status
Subject Bamboo, Florida E115119 entity
Predicate hasName P744 FINISHED
Object Bamboo
Bamboo is a fast-growing, woody grass known for its tall, hollow stems and widespread use in construction, crafts, and as an ornamental plant.
 E493288 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: Bamboo | Statement: [Bamboo, Florida, hasName, Bamboo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bamboo
Context triple: [Bamboo, Florida, hasName, Bamboo]
  • A. Sakao
    Sakao is an Oceanic language spoken on the island of Espiritu Santo in Vanuatu, noted for its complex phonology and distinctive sound changes.
  • B. Thốt Nốt
    Thốt Nốt is an urban district of Cần Thơ in Vietnam’s Mekong Delta, known for its agricultural landscape and growing urban development.
  • C. Talin
    Talin is a small town in western Armenia known for its historic churches and its location near Mount Aragats.
  • D. Bagassa
    Bagassa is a small genus of tropical trees in the mulberry family, known for species such as Bagassa guianensis found in South American rainforests.
  • E. Boehmeria
    Boehmeria is a genus of flowering plants commonly known for species like ramie, which are cultivated for their strong, fibrous stems used in textile production.
  • 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: Bamboo
Triple: [Bamboo, Florida, hasName, Bamboo]
Generated description
Bamboo is a fast-growing, woody grass known for its tall, hollow stems and widespread use in construction, crafts, and as an ornamental plant.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bamboo
Target entity description: Bamboo is a fast-growing, woody grass known for its tall, hollow stems and widespread use in construction, crafts, and as an ornamental plant.
  • A. Sakao
    Sakao is an Oceanic language spoken on the island of Espiritu Santo in Vanuatu, noted for its complex phonology and distinctive sound changes.
  • B. Thốt Nốt
    Thốt Nốt is an urban district of Cần Thơ in Vietnam’s Mekong Delta, known for its agricultural landscape and growing urban development.
  • C. Talin
    Talin is a small town in western Armenia known for its historic churches and its location near Mount Aragats.
  • D. Bagassa
    Bagassa is a small genus of tropical trees in the mulberry family, known for species such as Bagassa guianensis found in South American rainforests.
  • E. Boehmeria
    Boehmeria is a genus of flowering plants commonly known for species like ramie, which are cultivated for their strong, fibrous stems used in textile production.
  • 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd75a8ee7881908876859402911e5a completed March 20, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba9a19d881909f26b327273a95f1 completed March 21, 2026, 3:34 p.m.
NEDg Description generation batch_69bebb0c54c4819089eca12aae6e7613 completed March 21, 2026, 3:36 p.m.
NED2 Entity disambiguation (via description) batch_69bebb6fd0b08190a79a42e93689186b completed March 21, 2026, 3:38 p.m.
Created at: March 20, 2026, 1:41 p.m.