Triple
T11721488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Ford |
E278642
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Iris
Iris is a feminine given name of Greek origin, associated with the mythological goddess of the rainbow and often used in English-speaking countries.
|
E380721
|
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: Iris | Statement: [Mary Ford, givenName, Iris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iris Context triple: [Mary Ford, givenName, Iris]
-
A.
Iris
Iris is a recurring character on the satirical sketch comedy series "Portlandia," known for embodying the show's quirky, offbeat humor.
-
B.
Iris
"Iris" is a hit power ballad by the Goo Goo Dolls, best known for its prominent feature on the soundtrack of the film "City of Angels."
-
C.
Iris
Iris is the underage prostitute whom Travis Bickle becomes obsessed with rescuing in Martin Scorsese’s film "Taxi Driver."
-
D.
Iris
Iris is a large and diverse genus of flowering plants known for its showy, often multicolored blooms and sword-shaped leaves, widely cultivated as ornamentals in gardens worldwide.
-
E.
Iris
Iris is an Italian verismo opera by Pietro Mascagni, first performed in 1898 and noted for its exotic Japanese setting and lush orchestration.
- 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: Iris Triple: [Mary Ford, givenName, Iris]
Generated description
Iris is a feminine given name of Greek origin, associated with the mythological goddess of the rainbow and often used in English-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Iris Target entity description: Iris is a feminine given name of Greek origin, associated with the mythological goddess of the rainbow and often used in English-speaking countries.
-
A.
Iris
chosen
Iris is a feminine given name used in various cultures, often associated with the Greek goddess of the rainbow and the iris flower.
-
B.
Iris
Iris is a large and diverse genus of flowering plants known for its showy, often multicolored blooms and sword-shaped leaves, widely cultivated as ornamentals in gardens worldwide.
-
C.
Iris
Iris is a powerful, genetically engineered kaiju and one of Gamera’s most formidable adversaries in the Heisei-era Gamera film series.
-
D.
Iris
Iris is a 2001 British biographical drama film about the life and relationships of novelist and philosopher Iris Murdoch.
-
E.
Iris
Iris is an Italian verismo opera by Pietro Mascagni, first performed in 1898 and noted for its exotic Japanese setting and lush orchestration.
- F. None of above.
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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4c373088190bc2ae77a1696d280 |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef83c8ac2c8190b3bba7db42734f3a |
completed | April 27, 2026, 3:42 p.m. |
| NEDg | Description generation | batch_69ef96b13be881908102ffa867f96c22 |
completed | April 27, 2026, 5:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69efb51113708190998b570c33b9d0e7 |
completed | April 27, 2026, 7:12 p.m. |
Created at: April 8, 2026, 9:40 p.m.