Triple
T3383281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Society for the Anthropology of Food and Nutrition |
E71236
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
SAFN
SAFN is a professional organization dedicated to advancing the anthropological study of food, nutrition, and related cultural practices.
|
E352747
|
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: SAFN | Statement: [Society for the Anthropology of Food and Nutrition, hasAbbreviation, SAFN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SAFN Context triple: [Society for the Anthropology of Food and Nutrition, hasAbbreviation, SAFN]
-
A.
SANEF
SANEF is a major French motorway concession and operating company responsible for managing and maintaining several toll highways in northern and eastern France.
-
B.
SAF
SAF is the three-letter IATA airport code for Santa Fe Regional Airport in Santa Fe, New Mexico.
-
C.
SFA
The SFA is the Scottish Football Association, the main governing body for football in Scotland.
-
D.
SAU
SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
-
E.
SAU
SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
- 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: SAFN Triple: [Society for the Anthropology of Food and Nutrition, hasAbbreviation, SAFN]
Generated description
SAFN is a professional organization dedicated to advancing the anthropological study of food, nutrition, and related cultural practices.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SAFN Target entity description: SAFN is a professional organization dedicated to advancing the anthropological study of food, nutrition, and related cultural practices.
-
A.
SANEF
SANEF is a major French motorway concession and operating company responsible for managing and maintaining several toll highways in northern and eastern France.
-
B.
SAF
SAF is the three-letter IATA airport code for Santa Fe Regional Airport in Santa Fe, New Mexico.
-
C.
SFA
The SFA is the Scottish Football Association, the main governing body for football in Scotland.
-
D.
SAU
SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
-
E.
SAU
SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
- 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_69ad85a8fd9c819095ecedf838d2bf1b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb5eb0d188190a94415498ba81c11 |
completed | March 8, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b33452d79081909bf6955289e0dece |
completed | March 12, 2026, 9:46 p.m. |
| NEDg | Description generation | batch_69b334f75e708190aed8b388c9ea55d2 |
completed | March 12, 2026, 9:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3359ab56881908e247ba54c7dd6c7 |
completed | March 12, 2026, 9:52 p.m. |
Created at: March 8, 2026, 3:14 p.m.