Triple
T10147123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hall of Languages |
E231730
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object |
HOL
HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
|
E844068
|
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: HOL | Statement: [Hall of Languages, hasNickname, HOL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HOL Context triple: [Hall of Languages, hasNickname, HOL]
-
A.
Hol
Hol is a small settlement located on the island of Tjeldøya in northern Norway.
-
B.
Hol
Hol is a rural municipality in Viken county, Norway, known for its mountainous landscapes, winter sports tourism, and traditional Norwegian culture.
-
C.
HL
HL is the vehicle registration code used on license plates for the German city of Lübeck.
-
D.
Ho
Ho is the given name of the Korean-born contemporary artist Do Ho Suh, known for his large-scale installations exploring space, memory, and identity.
-
E.
Ho
"Ho" is a track featured on Ludacris's debut studio album "Back for the First Time."
- 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: HOL Triple: [Hall of Languages, hasNickname, HOL]
Generated description
HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HOL Target entity description: HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
-
A.
Hol
Hol is a small settlement located on the island of Tjeldøya in northern Norway.
-
B.
Hol
Hol is a rural municipality in Viken county, Norway, known for its mountainous landscapes, winter sports tourism, and traditional Norwegian culture.
-
C.
HL
HL is the vehicle registration code used on license plates for the German city of Lübeck.
-
D.
Ho
Ho is the given name of the Korean-born contemporary artist Do Ho Suh, known for his large-scale installations exploring space, memory, and identity.
-
E.
Ho
"Ho" is a track featured on Ludacris's debut studio album "Back for the First Time."
- 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_69ca848364f881908a24366a6feec1db |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec011c24819089b456fc8b9ed80c |
completed | April 2, 2026, 4:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e62c1984819095fcb239f11731b4 |
completed | April 5, 2026, 10:46 p.m. |
| NEDg | Description generation | batch_69d2e73fd6988190a338a9e49dc3671b |
completed | April 5, 2026, 10:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2e8c9058c8190bfa5720397331fa1 |
completed | April 5, 2026, 10:57 p.m. |
Created at: March 30, 2026, 9:07 p.m.