Triple
T14459024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corpus Christi Army Depot |
E358532
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
CCAD
CCAD is the Corpus Christi Army Depot, a major U.S. Army facility specializing in the maintenance, repair, and overhaul of military aircraft and aviation components.
|
E1100364
|
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: CCAD | Statement: [Corpus Christi Army Depot, hasAbbreviation, CCAD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CCAD Context triple: [Corpus Christi Army Depot, hasAbbreviation, CCAD]
-
A.
CCA
CCA is the highest state court in Texas for criminal cases, serving as the court of last resort for all criminal matters in the state.
-
B.
CCA
CCA is the ICAO airline designator used to identify Air China in international aviation operations.
-
C.
CCA
CCA is a performing arts venue and cultural center located in Concord, New Hampshire, hosting concerts, theater, and community events.
-
D.
CCA
CCA is the commonly used abbreviation for the Canada Council for the Arts, Canada’s national public arts funding and advocacy agency.
-
E.
CCA
CCA is an independent, not-for-profit organization in Canada that conducts expert assessments to inform public policy and decision-making on scientific and scholarly issues.
- 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: CCAD Triple: [Corpus Christi Army Depot, hasAbbreviation, CCAD]
Generated description
CCAD is the Corpus Christi Army Depot, a major U.S. Army facility specializing in the maintenance, repair, and overhaul of military aircraft and aviation components.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CCAD Target entity description: CCAD is the Corpus Christi Army Depot, a major U.S. Army facility specializing in the maintenance, repair, and overhaul of military aircraft and aviation components.
-
A.
CCA
CCA is the highest state court in Texas for criminal cases, serving as the court of last resort for all criminal matters in the state.
-
B.
CCA
CCA is the ICAO airline designator used to identify Air China in international aviation operations.
-
C.
CCA
CCA is a performing arts venue and cultural center located in Concord, New Hampshire, hosting concerts, theater, and community events.
-
D.
CCA
CCA is the commonly used abbreviation for the Canada Council for the Arts, Canada’s national public arts funding and advocacy agency.
-
E.
CCA
CCA is an independent, not-for-profit organization in Canada that conducts expert assessments to inform public policy and decision-making on scientific and scholarly issues.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91aabebc819097eb61b2d81c9a91 |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd64935d8081908e5b0e80027948e0 |
completed | May 8, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_69fd65cf06308190bf7b6463bc109542 |
completed | May 8, 2026, 4:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd66476ab88190b2d410ced33ce34b |
completed | May 8, 2026, 4:27 a.m. |
Created at: April 10, 2026, 1:19 a.m.