Triple
T12368285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIGBED |
E294927
|
entity |
| Predicate | supportsConference |
P2576
|
FINISHED |
| Object |
HSCC
HSCC (Hybrid Systems: Computation and Control) is a leading international research conference focused on the theory and applications of hybrid and cyber-physical systems.
|
E978081
|
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: HSCC | Statement: [SIGBED, supportsConference, HSCC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HSCC Context triple: [SIGBED, supportsConference, HSCC]
-
A.
CSCC
CSCC is a public community college in Cleveland, Tennessee, offering two-year degree and certificate programs for local and regional students.
-
B.
SCC
SCC is the commonly used abbreviation for the MIT Schwarzman College of Computing, an interdisciplinary hub for computing and AI research and education.
-
C.
SCC
SCC is the abbreviated name of the SAARC Cultural Centre, an institution that promotes cultural cooperation among South Asian Association for Regional Cooperation member countries.
-
D.
SCC
SCC is the three-letter IATA airport code for Deadhorse Airport, which serves the Prudhoe Bay oil fields in northern Alaska.
-
E.
SCC
SCC is the commonly used abbreviation for the Supreme Court of Canada, the country's highest judicial authority.
- 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: HSCC Triple: [SIGBED, supportsConference, HSCC]
Generated description
HSCC (Hybrid Systems: Computation and Control) is a leading international research conference focused on the theory and applications of hybrid and cyber-physical systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HSCC Target entity description: HSCC (Hybrid Systems: Computation and Control) is a leading international research conference focused on the theory and applications of hybrid and cyber-physical systems.
-
A.
CSCC
CSCC is a public community college in Cleveland, Tennessee, offering two-year degree and certificate programs for local and regional students.
-
B.
SCC
SCC is the commonly used abbreviation for the MIT Schwarzman College of Computing, an interdisciplinary hub for computing and AI research and education.
-
C.
SCC
SCC is the abbreviated name of the SAARC Cultural Centre, an institution that promotes cultural cooperation among South Asian Association for Regional Cooperation member countries.
-
D.
SCC
SCC is the three-letter IATA airport code for Deadhorse Airport, which serves the Prudhoe Bay oil fields in northern Alaska.
-
E.
SCC
SCC is the commonly used abbreviation for the Supreme Court of Canada, the country's highest judicial authority.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa502988190ba170dee90d9f394 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62abdad1c8190b083791d60138f2a |
completed | May 2, 2026, 4:47 p.m. |
| NEDg | Description generation | batch_69f62be4de888190aac94d441748d295 |
completed | May 2, 2026, 4:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62d4d0b8881908aa6b67db7d14609 |
completed | May 2, 2026, 4:58 p.m. |
Created at: April 8, 2026, 9:54 p.m.