Triple
T2248980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia Science and Technology Campus |
E49571
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
VSTC
VSTC is the Virginia Science and Technology Campus of George Washington University, known for its research facilities and graduate programs in science, technology, and engineering.
|
E248127
|
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: VSTC | Statement: [Virginia Science and Technology Campus, shortName, VSTC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VSTC Context triple: [Virginia Science and Technology Campus, shortName, VSTC]
-
A.
VU
VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
-
B.
VUT
VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
-
C.
VTST
VTST is the station code for the Vermont/Sunset station on the Los Angeles Metro Rail system.
-
D.
VP&S
VP&S is the commonly used abbreviation for Columbia University Vagelos College of Physicians and Surgeons, a leading medical school in New York City.
-
E.
VolgSTU
VolgSTU is a major Russian technical university located in Volgograd, specializing in engineering, technology, and applied sciences.
- 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: VSTC Triple: [Virginia Science and Technology Campus, shortName, VSTC]
Generated description
VSTC is the Virginia Science and Technology Campus of George Washington University, known for its research facilities and graduate programs in science, technology, and engineering.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VSTC Target entity description: VSTC is the Virginia Science and Technology Campus of George Washington University, known for its research facilities and graduate programs in science, technology, and engineering.
-
A.
VU
VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
-
B.
VUT
VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
-
C.
VTST
VTST is the station code for the Vermont/Sunset station on the Los Angeles Metro Rail system.
-
D.
VP&S
VP&S is the commonly used abbreviation for Columbia University Vagelos College of Physicians and Surgeons, a leading medical school in New York City.
-
E.
VolgSTU
VolgSTU is a major Russian technical university located in Volgograd, specializing in engineering, technology, and applied sciences.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ef74988190a0af51d983cf5658 |
completed | March 7, 2026, 6:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6b1719c481909ec3ff03d2a6f3bd |
completed | March 9, 2026, 6:39 a.m. |
| NEDg | Description generation | batch_69ae6bcfd2c481908f69df77f40655e2 |
completed | March 9, 2026, 6:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae6c4d9c04819086e3091bbbf16099 |
completed | March 9, 2026, 6:44 a.m. |
Created at: March 4, 2026, 7:47 p.m.