Triple
T15538198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School of Advanced Warfighting |
E370403
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
SAW
SAW is the abbreviation for the U.S. Marine Corps’ School of Advanced Warfighting, an advanced professional military education institution focused on developing operational-level planners and leaders.
|
E1162152
|
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: SAW | Statement: [School of Advanced Warfighting, hasAbbreviation, SAW]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SAW Context triple: [School of Advanced Warfighting, hasAbbreviation, SAW]
-
A.
SAW
SAW is the IATA airport code for Sabiha Gökçen International Airport, a major international airport serving Istanbul, Turkey.
-
B.
SA3
SA3 is the 3GPP security working group responsible for specifying and evolving security architecture and mechanisms across mobile communication standards.
-
C.
SAV
SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
-
D.
SAV
SAV is the IATA airport code for Savannah/Hilton Head International Airport serving Savannah, Georgia, and the surrounding region.
-
E.
SAAV
SAAV is the ICAO airport code for Sauce Viejo Airport, which serves the Santa Fe region in Argentina.
- 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: SAW Triple: [School of Advanced Warfighting, hasAbbreviation, SAW]
Generated description
SAW is the abbreviation for the U.S. Marine Corps’ School of Advanced Warfighting, an advanced professional military education institution focused on developing operational-level planners and leaders.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SAW Target entity description: SAW is the abbreviation for the U.S. Marine Corps’ School of Advanced Warfighting, an advanced professional military education institution focused on developing operational-level planners and leaders.
-
A.
SAW
SAW is the IATA airport code for Sabiha Gökçen International Airport, a major international airport serving Istanbul, Turkey.
-
B.
SA3
SA3 is the 3GPP security working group responsible for specifying and evolving security architecture and mechanisms across mobile communication standards.
-
C.
SAV
SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
-
D.
SAV
SAV is the IATA airport code for Savannah/Hilton Head International Airport serving Savannah, Georgia, and the surrounding region.
-
E.
SAAV
SAAV is the ICAO airport code for Sauce Viejo Airport, which serves the Santa Fe region in Argentina.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442f3c688190a599165e526af2ed |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d626e688190bd93481cfd6cb255 |
completed | May 9, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69ff3f075bb881908c254137ca7c3f9f |
completed | May 9, 2026, 2:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff3f87f788819080eccae52b0df145 |
completed | May 9, 2026, 2:07 p.m. |
Created at: April 10, 2026, 4:07 a.m.