Triple
T440137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moss Hart |
E10096
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Moss
Moss is a masculine given name most notably borne by American playwright and director Moss Hart.
|
E55150
|
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: Moss | Statement: [Moss Hart, givenName, Moss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moss Context triple: [Moss Hart, givenName, Moss]
-
A.
Moss
Moss is a coastal town and municipality in southeastern Norway known for its industrial history, cultural life, and role as a regional hub in Østfold.
-
B.
Shadowmoss
Shadowmoss is a tram stop on the Manchester Metrolink network in the Wythenshawe area of Greater Manchester, England.
-
C.
Muck
Muck is one of the Small Isles of Scotland, a tiny Inner Hebridean island known for its rugged coastline, wildlife, and remote rural character.
-
D.
Greenleaf
Greenleaf is the middle name of the 19th-century American Quaker poet and abolitionist John Greenleaf Whittier.
-
E.
The Stump
The Stump is the popular nickname for the towering parish church of St Botolph in Boston, Lincolnshire, renowned for its massive, landmark tower visible for miles across the flat surrounding landscape.
- 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: Moss Triple: [Moss Hart, givenName, Moss]
Generated description
Moss is a masculine given name most notably borne by American playwright and director Moss Hart.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Moss Target entity description: Moss is a masculine given name most notably borne by American playwright and director Moss Hart.
-
A.
Moss
Moss is a coastal town and municipality in southeastern Norway known for its industrial history, cultural life, and role as a regional hub in Østfold.
-
B.
Shadowmoss
Shadowmoss is a tram stop on the Manchester Metrolink network in the Wythenshawe area of Greater Manchester, England.
-
C.
Muck
Muck is one of the Small Isles of Scotland, a tiny Inner Hebridean island known for its rugged coastline, wildlife, and remote rural character.
-
D.
Greenleaf
Greenleaf is the middle name of the 19th-century American Quaker poet and abolitionist John Greenleaf Whittier.
-
E.
The Stump
The Stump is the popular nickname for the towering parish church of St Botolph in Boston, Lincolnshire, renowned for its massive, landmark tower visible for miles across the flat surrounding landscape.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef2977888190a0590b2c1bd2f5da |
completed | Feb. 28, 2026, 1:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4366fc48c8190a10f1034a2bb579c |
completed | March 1, 2026, 12:51 p.m. |
| NEDg | Description generation | batch_69a436b31fc8819081b0a7b49a1ad3cc |
completed | March 1, 2026, 12:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a43755152881909a4dfa8b31a0aad6 |
completed | March 1, 2026, 12:55 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.