Triple
T10329960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geography Markup Language |
E242848
|
entity |
| Predicate | relatedStandard |
P37
|
FINISHED |
| Object |
SFS
SFS is a spatial feature standard that defines how geographic features and their properties are modeled and accessed in geospatial information systems.
|
E856252
|
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: SFS | Statement: [Geography Markup Language, relatedStandard, SFS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SFS Context triple: [Geography Markup Language, relatedStandard, SFS]
-
A.
SFS
SFS is the abbreviation for the Senior Foreign Service, the elite cadre of senior-ranking career diplomats in the United States Foreign Service.
-
B.
SFS
SFS is a renowned Georgetown University school specializing in international affairs, diplomacy, and global policy education.
-
C.
SFS
SFS is the commonly used abbreviation for the San Francisco Symphony, a major American orchestra based in San Francisco, California.
-
D.
SFS Media
SFS Media is the in-house recording label of the San Francisco Symphony, known for producing high-quality orchestral and classical music recordings.
-
E.
FSSF
FSSF is the abbreviation for the F# Software Foundation, a community-driven organization that supports and promotes the F# programming language and its ecosystem.
- 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: SFS Triple: [Geography Markup Language, relatedStandard, SFS]
Generated description
SFS is a spatial feature standard that defines how geographic features and their properties are modeled and accessed in geospatial information systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SFS Target entity description: SFS is a spatial feature standard that defines how geographic features and their properties are modeled and accessed in geospatial information systems.
-
A.
SFS
SFS is a renowned Georgetown University school specializing in international affairs, diplomacy, and global policy education.
-
B.
SFS
SFS is the abbreviation for the Senior Foreign Service, the elite cadre of senior-ranking career diplomats in the United States Foreign Service.
-
C.
SFS
SFS is the commonly used abbreviation for the San Francisco Symphony, a major American orchestra based in San Francisco, California.
-
D.
SFS Media
SFS Media is the in-house recording label of the San Francisco Symphony, known for producing high-quality orchestral and classical music recordings.
-
E.
FSSF
FSSF is the abbreviation for the F# Software Foundation, a community-driven organization that supports and promotes the F# programming language and its ecosystem.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7fb77348190ac8ff887f6f03450 |
completed | April 7, 2026, 10:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71dbc7df48190b8a11a92f946fd30 |
completed | April 9, 2026, 3:32 a.m. |
| NEDg | Description generation | batch_69d73189d7cc8190b81bb30994b3900f |
completed | April 9, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7329891688190b5c1ec5906728f01 |
completed | April 9, 2026, 5:01 a.m. |
Created at: April 6, 2026, 11:52 a.m.