Triple

T4420927
Position Surface form Disambiguated ID Type / Status
Subject Humanitarian Data Exchange E95093 entity
Predicate supportsStandard P1587 FINISHED
Object HXL
HXL (Humanitarian Exchange Language) is a lightweight data standard designed to improve the interoperability, quality, and rapid sharing of humanitarian data across organizations and crises.
 E437574 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: HXL | Statement: [Humanitarian Data Exchange, supportsStandard, HXL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HXL
Context triple: [Humanitarian Data Exchange, supportsStandard, HXL]
  • A. HX
    HX is a postcode area in West Yorkshire, England, covering Halifax and surrounding towns including Hebden Bridge.
  • B. HLC
    HLC is the commonly used abbreviation for the Harvard Longwood Campus, a major Harvard University hub for medical and public health education and research in Boston.
  • C. Xelb
    Xelb is the former Arabic name for the Portuguese city of Silves, a historically significant town in the Algarve region.
  • D. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • E. XU
    XU was a clandestine Norwegian intelligence organization that gathered and transmitted vital information to the Allies during the German occupation in World War II.
  • 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: HXL
Triple: [Humanitarian Data Exchange, supportsStandard, HXL]
Generated description
HXL (Humanitarian Exchange Language) is a lightweight data standard designed to improve the interoperability, quality, and rapid sharing of humanitarian data across organizations and crises.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HXL
Target entity description: HXL (Humanitarian Exchange Language) is a lightweight data standard designed to improve the interoperability, quality, and rapid sharing of humanitarian data across organizations and crises.
  • A. HX
    HX is a postcode area in West Yorkshire, England, covering Halifax and surrounding towns including Hebden Bridge.
  • B. HLC
    HLC is the commonly used abbreviation for the Harvard Longwood Campus, a major Harvard University hub for medical and public health education and research in Boston.
  • C. Xelb
    Xelb is the former Arabic name for the Portuguese city of Silves, a historically significant town in the Algarve region.
  • D. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • E. XU
    XU was a clandestine Norwegian intelligence organization that gathered and transmitted vital information to the Allies during the German occupation in World War II.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35521e020819099e72b9e2ccbd36d completed March 13, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f62715748190abceb14396ad637d completed March 14, 2026, 11:58 p.m.
NEDg Description generation batch_69b5f6d4bb84819081512aec6b49507b completed March 15, 2026, 12:01 a.m.
NED2 Entity disambiguation (via description) batch_69b5f7887cb08190bf498eefc3627bfa completed March 15, 2026, 12:04 a.m.
Created at: March 12, 2026, 11:30 p.m.