Triple
T588783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glenn Research Center |
E17219
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
GRC
GRC is the commonly used abbreviation for NASA's Glenn Research Center, a major research facility focused on aeronautics and space technology.
|
E73768
|
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: GRC | Statement: [Glenn Research Center, hasAbbreviation, GRC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GRC Context triple: [Glenn Research Center, hasAbbreviation, GRC]
-
A.
GRG
GRG is the standard abbreviation for the Grand Rapids Griffins, a professional ice hockey team in the American Hockey League.
-
B.
RGC
RGC was the stock ticker symbol for Regal Entertainment Group, a major American movie theater chain operator.
-
C.
GPC
GPC is the GNU Pascal Compiler, a free, open-source Pascal compiler that is part of the GNU Compiler Collection (GCC) project.
-
D.
RMC
RMC is the Royal Military College at Duntroon, Australia’s principal officer training academy for the Australian Army.
-
E.
GLC
GLC is a Chicago-based rapper and longtime Kanye West collaborator known for his appearances on early Kanye albums and his affiliation with the G.O.O.D. Music collective.
- 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: GRC Triple: [Glenn Research Center, hasAbbreviation, GRC]
Generated description
GRC is the commonly used abbreviation for NASA's Glenn Research Center, a major research facility focused on aeronautics and space technology.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GRC Target entity description: GRC is the commonly used abbreviation for NASA's Glenn Research Center, a major research facility focused on aeronautics and space technology.
-
A.
GRG
GRG is the standard abbreviation for the Grand Rapids Griffins, a professional ice hockey team in the American Hockey League.
-
B.
RGC
RGC was the stock ticker symbol for Regal Entertainment Group, a major American movie theater chain operator.
-
C.
GPC
GPC is the GNU Pascal Compiler, a free, open-source Pascal compiler that is part of the GNU Compiler Collection (GCC) project.
-
D.
RMC
RMC is the Royal Military College at Duntroon, Australia’s principal officer training academy for the Australian Army.
-
E.
GLC
GLC is a Chicago-based rapper and longtime Kanye West collaborator known for his appearances on early Kanye albums and his affiliation with the G.O.O.D. Music collective.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9d1e68819096a9b5e7b2e83d6e |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5103be4b881908fcd20c4c781c0a0 |
completed | March 2, 2026, 4:21 a.m. |
| NEDg | Description generation | batch_69a5140f86148190b9f3dd70fa6b0f42 |
completed | March 2, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5146662488190b2d9024d6d999fa3 |
completed | March 2, 2026, 4:39 a.m. |
Created at: March 1, 2026, 7:33 p.m.