Triple
T8480084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gloria Fault |
E200491
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Gloria (oceanographic name context)
Gloria is an oceanographic research vessel whose name was given to the Gloria Fault, a major tectonic feature in the North Atlantic.
|
E737473
|
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: Gloria (oceanographic name context) | Statement: [Gloria Fault, namedAfter, Gloria (oceanographic name context)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gloria (oceanographic name context) Context triple: [Gloria Fault, namedAfter, Gloria (oceanographic name context)]
-
A.
Tess Ocean
Tess Ocean is a central character in the Ocean's film series, known as Danny Ocean's sophisticated and sharp-witted ex-wife who becomes entangled in his elaborate heists.
-
B.
Okeanos
Okeanos is the primordial Greek god personifying the great encircling river believed to surround the world.
-
C.
Océan
Océan was a prominent French ship of the line that served as a flagship in major naval engagements during the age of sail.
-
D.
Océan
Océan is a coastal department in Cameroon's South Region, known for its Atlantic shoreline and port towns.
-
E.
Oceano
Oceano is a small coastal community in California known for its dunes, beaches, and outdoor recreation.
- 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: Gloria (oceanographic name context) Triple: [Gloria Fault, namedAfter, Gloria (oceanographic name context)]
Generated description
Gloria is an oceanographic research vessel whose name was given to the Gloria Fault, a major tectonic feature in the North Atlantic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gloria (oceanographic name context) Target entity description: Gloria is an oceanographic research vessel whose name was given to the Gloria Fault, a major tectonic feature in the North Atlantic.
-
A.
Tess Ocean
Tess Ocean is a central character in the Ocean's film series, known as Danny Ocean's sophisticated and sharp-witted ex-wife who becomes entangled in his elaborate heists.
-
B.
Okeanos
Okeanos is the primordial Greek god personifying the great encircling river believed to surround the world.
-
C.
Océan
Océan was a prominent French ship of the line that served as a flagship in major naval engagements during the age of sail.
-
D.
Océan
Océan is a coastal department in Cameroon's South Region, known for its Atlantic shoreline and port towns.
-
E.
Oceano
Oceano is a small coastal community in California known for its dunes, beaches, and outdoor recreation.
- 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5232d008190ae55b982f5fc9e8b |
completed | March 31, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce3a22d6e481908bdb0b9cc0df0113 |
completed | April 2, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_69ce3cddba648190be303823862a0423 |
completed | April 2, 2026, 9:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce3d5edabc8190b985546b8242e90a |
completed | April 2, 2026, 9:56 a.m. |
Created at: March 30, 2026, 6:12 p.m.