Triple
T13209011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange, Texas |
E314437
|
entity |
| Predicate | originalName |
P65
|
FINISHED |
| Object |
Green’s Bluff
Green’s Bluff is the former name of the city now known as Orange in southeastern Texas, near the Louisiana border.
|
E1027452
|
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: Green’s Bluff | Statement: [Orange, Texas, originalName, Green’s Bluff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Green’s Bluff Context triple: [Orange, Texas, originalName, Green’s Bluff]
-
A.
Barn Bluff
Barn Bluff is a prominent, rugged mountain peak in Tasmania, Australia, known for its striking dolerite cliffs and popular hiking routes within the Cradle Mountain-Lake St Clair region.
-
B.
Birchleigh
Birchleigh is a residential suburb within the city of Kempton Park in Gauteng, South Africa.
-
C.
Tenneville
Tenneville is a rural municipality in the Ardennes region of southern Belgium, known for its forests and small villages.
-
D.
Grandad Bluff
Grandad Bluff is a prominent scenic overlook and natural landmark in La Crosse, Wisconsin, known for its panoramic views of the city and the Mississippi River valley.
-
E.
Fort Hawkins
Fort Hawkins was an early 19th-century U.S. military fort and frontier trading post that became the nucleus for the later city of Macon, Georgia.
- 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: Green’s Bluff Triple: [Orange, Texas, originalName, Green’s Bluff]
Generated description
Green’s Bluff is the former name of the city now known as Orange in southeastern Texas, near the Louisiana border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Green’s Bluff Target entity description: Green’s Bluff is the former name of the city now known as Orange in southeastern Texas, near the Louisiana border.
-
A.
Barn Bluff
Barn Bluff is a prominent, rugged mountain peak in Tasmania, Australia, known for its striking dolerite cliffs and popular hiking routes within the Cradle Mountain-Lake St Clair region.
-
B.
Birchleigh
Birchleigh is a residential suburb within the city of Kempton Park in Gauteng, South Africa.
-
C.
Tenneville
Tenneville is a rural municipality in the Ardennes region of southern Belgium, known for its forests and small villages.
-
D.
Grandad Bluff
Grandad Bluff is a prominent scenic overlook and natural landmark in La Crosse, Wisconsin, known for its panoramic views of the city and the Mississippi River valley.
-
E.
Fort Hawkins
Fort Hawkins was an early 19th-century U.S. military fort and frontier trading post that became the nucleus for the later city of Macon, Georgia.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c9e072c8190b66e2c2430628ed0 |
completed | April 10, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f611b11c8190b9f89313eb2b5fab |
completed | May 3, 2026, 7:15 a.m. |
| NEDg | Description generation | batch_69f6f79703588190ba088971da54340f |
completed | May 3, 2026, 7:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6f89072a88190b3182f581b1b6762 |
completed | May 3, 2026, 7:26 a.m. |
Created at: April 9, 2026, 9:17 p.m.